Feature Extraction & Image Processing for Computer Vision

By

  • Mark Nixon, Professor of Electronics and Computer Science at the University of Southampton, UK.

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.

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Audience

University researchers, Research & Development engineers, graduate students.

 

Book information

  • Published: August 2012
  • Imprint: ACADEMIC PRESS
  • ISBN: 978-0-12-396549-3

Reviews

"…the book is well written and is easy to follow. In fact, the presentation order is the logical order of any actual computer vision system processing pipeline. The authors have done a great job grouping related topics together and touching upon recent techniques."--IAPR Newsletter, October 2013
"The mathematical element is presented in a non-mathematical way thus making the content more accessible…this edition is a very welcome addition to vision extraction."--IMA.org, August 2013
"All in all, I highly recommend this 600 pager as an introduction for students, and as a reference for practitioners. The latter audience will find an abundance of use references in each chapter…"--ComputingReviews.com, April 18, 2013
"After reviewing the human vision system, Nixon…and Aguardo…introduce signal processing theory for computer vision and current digital techniques for edge detection within an image, fixed shape matching, and deformable shape analysis. The undergraduate engineering textbook also explains the characterization of objects by boundary, region, and texture descriptions."--Reference and Research Book News, February 2013




Table of Contents

Preface
1. Introduction
2. Images, Sampling and Frequency Domain Processing
3. Basic Image Processing Operations
4. Low-Level Feature Extraction (including Edge Detection)
5. High-Level Feature Extraction: Fixed Shape Matching
6. High-Level Feature Extraction: Deformable Shape Analysis
7. Object Description
8. Introduction to Texture Description, Segmentation and Classification
9. Moving Object Detection and Description
10. Appendix 1: Camera Geometry Fundamentals
11. Appendix 2: Least Squares Analysis
12. Appendix 3: Principal Components Analysis
13. Appendix 4: Colour Images
References
Index