DUBLIN--(BUSINESS WIRE)-- Research and Markets (http://www.researchandmarkets.com/research/x27d7s/feature) has announced the addition of Elsevier Science and Technology's new book "Feature Extraction & Image Processing for Computer Vision. Edition No. 3" to their offering.
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.
- 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
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
Appendix 1: Camera Geometry Fundamentals
Appendix 2: Least Squares Analysis
Appendix 3: Principal Components Analysis
Appendix 4: Colour Images References Index
Aguado, Alberto S
For more information visit http://www.researchandmarkets.com/research/x27d7s/feature
Source: Elsevier Science and Technology
Source: Research and Markets