| Title : | Feature extraction & image processing for computer vision | | Material Type: | printed text | | Authors: | Mark S. Nixon, Author ; Alberto S. Aguado, Author | | Publisher: | Elsevier/Academic Press, (Amsterdam -London) | | Publication Date: | 2012 | | Pagination: | xvii, 607 p. | | Layout: | ill. | | Size: | 24 cm | | ISBN (or other code): | 978-0-12-396549-3 | | General note: | Includes bibliographical references
Includes index (p. 601-607) | | Languages : | English (eng) Original Language : English (eng) | | Descriptors: | Computer graphics
Computer vision
Image processing - Digital techniques
Pattern recognition systems - Data processing
| | Class number: | 006.6 | | Abstract: | 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, Ada boost, and a new appendix on color models. Coverage of distance measures, feature detectors, wavelets, level sets and texture tutorials has been extended. | | Contents note: | Images, Sampling, and Frequency Domain Processing; Basic Image Processing Operations; Low-Level Feature Extraction (including edge detection); High-Level Feature Extraction: Fixed Shape Matching; High-Level Feature Extraction : Deform able Shape Analysis; Object Description; Introduction to Texture Description, Segmentation, and Classification; Moving Object Detection and and Description; | | Record link: | https://library.seeu.edu.mk/index.php?lvl=notice_display&id=16230 |
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