Feature Extraction & Image Processing for Computer Vision, Third Edition
- 9h 43m
- Alberto S. Aguado, Mark S. Nixon
- Elsevier Science and Technology Books, Inc.
- 2012
This book is an essential guide to the implementation of image processing and computer vision techniques, with tutorial introductions and sample code in Matlab. Algorithms are presented and fully explained to enable complete understanding of the methods and techniques demonstrated. As one reviewer noted, "The main strength of the proposed book is the exemplar code of the algorithms."
Fully updated with the latest developments in feature extraction, including expanded tutorials and new techniques, this new edition contains extensive new material on Haar wavelets, Viola-Jones, bilateral filtering, SURF, PCA-SIFT, moving object detection and tracking, development of symmetry operators, LBP texture analysis, Adaboost, and a new appendix on color models. Coverage of distance measures, feature detectors, wavelets, level sets and texture tutorials has been extended.
- Named a 2012 Notable Computer Book for Computing Methodologies by Computing Reviews
- Essential reading for engineers and students working in this cutting-edge field
- Ideal module text and background reference for courses in image processing and computer vision
- The only currently available text to concentrate on feature extraction with working implementation and worked through derivation
In this Book
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Introduction
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Images, Sampling, and Frequency Domain Processing
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Basic Image Processing Operations
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Low-Level Feature Extraction (Including Edge Detection)
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High-Level Feature Extraction—Fixed Shape Matching
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High-Level Feature Extraction—Deformable Shape Analysis
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Object Description
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Introduction to Texture Description, Segmentation, and Classification
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Moving Object Detection and Description
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Appendix 1—Camera Geometry Fundamentals
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Appendix 2—Least Squares Analysis
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Appendix 3—Principal Components Analysis
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Appendix 4—Color Images
