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Feature Extraction and Image Processing for Computer Vision Paperback – 3 Aug 2012
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"…the book is well written and is easy to follow. In fact, the presentation order is the logical order of any actual computer vision system processing pipeline. The authors have done a great job grouping related topics together and touching upon recent techniques."--IAPR Newsletter, October 2013 "The mathematical element is presented in a non-mathematical way thus making the content more accessible…this edition is a very welcome addition to vision extraction."--IMA.org, August 2013 "All in all, I highly recommend this 600 pager as an introduction for students, and as a reference for practitioners. The latter audience will find an abundance of use references in each chapter…"--ComputingReviews.com, April 18, 2013 "After reviewing the human vision system, Nixon…and Aguardo…introduce signal processing theory for computer vision and current digital techniques for edge detection within an image, fixed shape matching, and deformable shape analysis. The undergraduate engineering textbook also explains the characterization of objects by boundary, region, and texture descriptions."--Reference and Research Book News, February 2013
About the Author
Mark Nixon is the Professor in Computer Vision at the University of Southampton UK. His research interests are in image processing and computer vision. His team develops new techniques for static and moving shape extraction which have found application in biometrics and in medical image analysis. His team were early workers in automatic face recognition, later came to pioneer gait recognition and more recently joined the pioneers of ear biometrics. With Tieniu Tan and Rama Chellappa, their book Human ID based on Gait is part of the Springer Series on Biometrics and was published in 2005. He has chaired/ program chaired many conferences (BMVC 98, AVBPA 03, IEEE Face and Gesture FG06, ICPR 04, ICB 09, IEEE BTAS 2010) and given many invited talks. Dr. Nixon is a Fellow IET and a Fellow IAPR.
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It does this by including unnecessarily formalized mathematics when it's really the intuition that is required (but hey, probably gets bonus academic points for this) or by referring back to formulas defined 20-odd pages ago every few words, causing you to constantly have to flick back to move forward. Of course, then you realize the formula it's referring to is guilty of the first issue and is exceedingly simple, or perhaps not even really required to understand the topic anyway.
I don't think the basic is suited for teaching, or enhancing understanding if i'm honest. I think it's a book by seasoned computer vision academics, for seasoned computer vision academics. Anyone else could probably find better material elsewhere.
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However, it is better as a handbook for experts, rather than as a textbook for students. Notations are not consistent across chapters or sections, and some of them are quite weird. For example, v, v', v'' denote trajectory, velocity and acceleration in the discussion of curvature. I would prefer p, v, a. Also, a few equations contain errors, which inexperienced students cannot find easily.
There are too many errors and some paragraphs are simply not understandable. The book needs serious editing.