Digital image processing

By:

Gonzalez, Rafael C

Contributor(s):

Woods, Richard E [Co-author]

Publication details: Noida: Pearson Education, 2018.Edition: 4th edDescription: 1019p. col. ill; pbk: 25cmISBN:

9789353062989

Subject(s):

DDC classification:

621.367 GON

Summary: A complete update of the image pattern recognition chapter to incorporate new material, including deep neural networks, backpropagation, deep learning, and, especially, deep convolutional neural networks. Expanded coverage of feature extraction, including maximally stable extremal regions, and the Scale Invariant Feature Transform (SIFT). A discussion of superpixels and their use in region segmentation. Coverage of graph cuts and their application to segmentation. An introduction to segmentation using active contours (snakes and level sets). New material related to histogram matching. Expanded coverage of the fundamentals of spatial filtering. A more comprehensive and cohesive coverage of image transforms. A more complete presentation of finite differences, with a focus on edge detection. More homework problems at the end of the chapters. More examples. MATLAB computer projects. pearson.com/en-us/subject-catalog/p/digital-image-processing/P200000003224?view=educator

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Item type	Current library	Collection	Call number	Copy number	Status	Date due	Barcode
Books	IIT Gandhinagar	General	621.367 GON (Browse shelf(Opens below))	1	Available		033096

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Includes bibliographical references and index

A complete update of the image pattern recognition chapter to incorporate new material, including deep neural networks, backpropagation, deep learning, and, especially, deep convolutional neural networks. Expanded coverage of feature extraction, including maximally stable extremal regions, and the Scale Invariant Feature Transform (SIFT). A discussion of superpixels and their use in region segmentation. Coverage of graph cuts and their application to segmentation. An introduction to segmentation using active contours (snakes and level sets). New material related to histogram matching. Expanded coverage of the fundamentals of spatial filtering. A more comprehensive and cohesive coverage of image transforms. A more complete presentation of finite differences, with a focus on edge detection. More homework problems at the end of the chapters. More examples. MATLAB computer projects.

pearson.com/en-us/subject-catalog/p/digital-image-processing/P200000003224?view=educator

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