
- 632 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
eBook - ePub
Feature Extraction and Image Processing for Computer Vision
About this book
Feature Extraction and Image Processing for Computer Vision 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
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Please note we cannot support devices running on iOS 13 and Android 7 or earlier. Learn more about using the app.
Yes, you can access Feature Extraction and Image Processing for Computer Vision by Mark Nixon in PDF and/or ePUB format, as well as other popular books in Computer Science & Computer Vision & Pattern Recognition. We have over one million books available in our catalogue for you to explore.
Information
Table of contents
- Cover image
- Title page
- Table of Contents
- Dedication
- Copyright
- Preface
- About the authors
- Chapter 1. Introduction
- Chapter 2. Images, sampling, and frequency domain processing
- Chapter 3. Basic image processing operations
- Chapter 4. Low-level feature extraction (including edge detection)
- Chapter 5. High-level feature extraction: fixed shape matching
- Chapter 6. High-level feature extraction: deformable shape analysis
- Chapter 7. Object description
- Chapter 8. Introduction to texture description, segmentation, and classification
- Chapter 9. Moving object detection and description
- Chapter 10. Appendix 1: Camera geometry fundamentals
- Chapter 11. Appendix 2: Least squares analysis
- Chapter 12. Appendix 3: Principal components analysis
- Chapter 13. Appendix 4: Color images
- Index