03103nam a22003257a 4500 20136365 SA-PMU 20260217101931.0 260217b ||||| |||| 00| 0 eng d 2017049755 9780128149768 h/c 9780128149768 DLC eng DLC rda DLC pcc TA1634 .N59 2020 006.3/7 23 Feature extraction and image processing for computer vision / Mark S. Nixon, Electronics and Computer Science, University of Southampton ; Alberto S. Aguado, Foundry, London. Academic Press Engineering Science Reference, 2020 632 pages ; text txt rdacontent unmediated n rdamedia volume nc rdacarrier 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. Includes index. 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. - The only text to concentrate on feature extraction with working implementation and worked through mathematical derivations and algorithmic methods - A thorough overview of available feature extraction methods including essential background theory, shape methods, texture and deep learning - Up to date coverage of interest point detection, feature extraction and description and image representation (including frequency domain and colour) - Good balance between providing a mathematical background and practical implementation - Detailed and explanatory of algorithms in MATLAB and Python Computer vision. 7 cbc orignew 1 ecip 20 y-gencatlg lcc BOOK 12880 12880 0 0 lcc 0 0 MAIN MAIN 2026-02-17 0 TA1634 .N59 2020 51952000265634 2026-02-17 2026-02-17 BOOK 0 0 lcc 0 0 MAIN FEMALE 2026-02-17 0 TA1634 .N59 2020 51952000265900 2026-02-17 2026-02-17 BOOK