Feature Extraction and Image Processing for Computer Vision



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 ReviewsEssential reading for engineers and students working in this cutting edge fieldIdeal module text and background reference for courses in image processing and computer visionThe only currently available text to concentrate on feature extraction with working implementation and worked through derivation New Download [ Feature Extraction and Image Processing for Computer Vision ] Author [ Mark S. Nixon ] For Kindle ePUB or eBook – tiffanydaniels.co.ukFeature Extraction and Image Processing for Computer Vision

Is a well-known author, some of his books are a fascination for readers like in the Feature Extraction and Image Processing for Computer Vision book, this is one of the most wanted Mark S. Nixon author readers around the world.

Download Feature Extraction and Image Processing for Computer Vision  – tiffanydaniels.co.uk
  • Paperback
  • 632 pages
  • Feature Extraction and Image Processing for Computer Vision
  • Mark S. Nixon
  • English
  • 14 June 2018
  • 0123965497

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