Feature Extraction & Image Processing for Computer Vision

Feature Extraction & Image Processing for Computer Vision

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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 derivationshow more

Product details

  • Paperback | 632 pages
  • 188 x 232 x 38mm | 1,161.19g
  • Elsevier Science Publishing Co Inc
  • Academic Press Inc
  • San Diego, United States
  • English
  • 3rd Revised edition
  • 0123965497
  • 9780123965493
  • 478,000

Review quote

".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 2013show more

About Mark Nixon (Ph

Mark Nixon is the Professor in Computer Vision at the University of Southampton UK. His research interests are in image processing and computer vision. His team develops new techniques for static and moving shape extraction which have found application in biometrics and in medical image analysis. His team were early workers in automatic face recognition, later came to pioneer gait recognition and more recently joined the pioneers of ear biometrics. With Tieniu Tan and Rama Chellappa, their book Human ID based on Gait is part of the Springer Series on Biometrics and was published in 2005. He has chaired/ program chaired many conferences (BMVC 98, AVBPA 03, IEEE Face and Gesture FG06, ICPR 04, ICB 09, IEEE BTAS 2010) and given many invited talks. Dr. Nixon is a Fellow IET and a Fellow IAPR.show more

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 Indexshow more