The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:

• Applications and tools for image processing, and fundamentals with several implementation examples
• Concepts of image formation
• OpenCV installation with step-by-step screen shots
• Concepts behind intensity, brightness and contrast, color models
• Ways by which noises are created in an image and the possible remedial measures
• Edge detection, image segmentation, classification, regression, classification algorithms
• Importance of frequency domain in image processing field
• Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding

The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study.

Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.