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{ "item_title" : "Feature Extraction and Image Processing for Computer Vision", "item_author" : [" Mark Nixon", "Alberto S. Aguado "], "item_description" : "Feature Extraction for Image Processing and Computer Vision is an essential guide to the implementation of image processing and computer vision techniques, with tutorial introductions and sample code in MATLAB and Python. 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 link between theory and exemplar code of the algorithms. Essential background theory is carefully explained. This text gives students and researchers in image processing and computer vision a complete introduction to classic and state-of-the art methods in feature extraction together with practical guidance on their implementation.", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/0/12/814/976/0128149760_b.jpg", "price_data" : { "retail_price" : "89.95", "online_price" : "89.95", "our_price" : "89.95", "club_price" : "89.95", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Feature Extraction and Image Processing for Computer Vision|Mark Nixon

Feature Extraction and Image Processing for Computer Vision

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Overview

Feature Extraction for Image Processing and Computer Vision is an essential guide to the implementation of image processing and computer vision techniques, with tutorial introductions and sample code in MATLAB and Python. 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 link between theory and exemplar code of the algorithms." Essential background theory is carefully explained.

This text gives students and researchers in image processing and computer vision a complete introduction to classic and state-of-the art methods in feature extraction together with practical guidance on their implementation.

This item is Non-Returnable

Details

  • ISBN-13: 9780128149768
  • ISBN-10: 0128149760
  • Publisher: Academic Press
  • Publish Date: November 2019
  • Dimensions: 9.25 x 7.5 x 1.31 inches
  • Shipping Weight: 2.43 pounds
  • Page Count: 650

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