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6 of 6 people found the following review helpful:
5.0 out of 5 stars Solid Foundation to computer Vision, February 19, 2002
By 
Gamal Seedahmed (Richland, WA United States) - See all my reviews
This review is from: Machine Vision, Second Edition: Theory, Algorithms, Practicalities (Signal Processing and its Applications) (Hardcover)
First of all I like this book very much. This book provides a solid and concrete foundation to computer vision from engineering point of view. The basic issues are treated very well in the conceptual and practical levels (e.g. edge detection). I came from a photogrammetry background, which means that the geometric aspects are very dominant in my thinking, and this book emphasize many geometric concepts in computer vision specially the treatment of Hough Transform as a main theme in the book. I recommend this book to the practitioners in spatial sciences (GIS, Remote sensing, Photogrammetry, etc) as well as the general community of computer vision.
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5 of 5 people found the following review helpful:
5.0 out of 5 stars Excellent resource, August 3, 2001
By 
Peter Jensen (Ann Arbor, Mi United States) - See all my reviews
This review is from: Machine Vision, Second Edition: Theory, Algorithms, Practicalities (Signal Processing and its Applications) (Hardcover)
Covers many aspects of vision, from basic image processing through high level scene analysis. It doesn't always go down to the nitty-gritty source code level for every topic, but it does provide the direction to handle most every common machine vision problem. Of the ten or so general machine vision books on my easy-access shelf, this is the one I seem to pull down the most.
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4 of 5 people found the following review helpful:
4.0 out of 5 stars Good structured reference, very useful, June 6, 2000
By A Customer
This review is from: Machine Vision, Second Edition: Theory, Algorithms, Practicalities (Signal Processing and its Applications) (Hardcover)
A very clearly structured book which is useful as a reference. Covers a lot of subjects (filtering, detection of shapes [lines, circles, holes and more], pattern matching/recognition, motion, invariants, ...), including the implementation aspects (hard/software). The chapters sometimes do not go much into deep but provide further references. Recommended book!
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Machine Vision, Second Edition: Theory, Algorithms, Practicalities (Signal Processing and its Applications)
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