Overview
- Over 130 illustrations throughout the text
- Detailed exercises at the end of each chapter
- Large number of examples, of specific images on which the theory is tested are included
- Includes supplementary material: sn.pub/extras
Part of the book series: Interdisciplinary Applied Mathematics (IAM, volume 34)
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Table of contents (15 chapters)
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Front Matter
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Back Matter
Keywords
About this book
This book introduces the reader to a recent theory in Computer Vision yielding elementary techniques to analyse digital images. These techniques are inspired from and are a mathematical formalization of the Gestalt theory. Gestalt theory, which had never been formalized is a rigorous realm of vision psychology developped between 1923 and 1975.
From the mathematical viewpoint the closest field to it is stochastic geometry, involving basic probability and statistics, in the context of image analysis.
The book is intended for a multidisciplinary audience of researchers and engineers. It is self contained in three aspects: mathematics, vision and algorithms, and requires only a background of elementary calculus and probability. A large number of illustrations, exercises and examples are included. The authors maintain a public software, MegaWave, containing implementations of most of the image analysis techniques developed in the book.
Reviews
From the reviews:
"This book tells the story of how to construct objects form images, in a way closely related to human perception. ... contains many illustrations and images that are analyzed, from various fields of applied science. ... References in the end, however, are helpful for further reading. ... To summarize, the book is a fine and timely introduction to a fascinating field of science. I can certainly recommend its reading to anyone dealing in a probabilistic sense with images ... ." (A. Stein, Kwantitatieve Methoden, Issue R09, 2008)
“This book is focused on Gestalt theory and image processing using probabilistic approaches. … carefully written with exercise problems in each chapter and can be used directly as a textbook on the topic. … This book is clearly written and relatively easy to read. The topics and directions are well thought out and can be used as a textbook for a graduate-level course on the topic. It is an interesting book on Gestalt theory and a good introduction to the meaningful events and related topics.” (Sung Ha Kang, SIAM Review, Vol. 52 (2), 2010)
Authors and Affiliations
Bibliographic Information
Book Title: From Gestalt Theory to Image Analysis
Book Subtitle: A Probabilistic Approach
Authors: Agnés Desolneux, Lionel Moisan, Jean-Michel Morel
Series Title: Interdisciplinary Applied Mathematics
DOI: https://doi.org/10.1007/978-0-387-74378-3
Publisher: Springer New York, NY
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer-Verlag New York 2008
Hardcover ISBN: 978-0-387-72635-9Published: 18 December 2007
Softcover ISBN: 978-1-4419-2481-0Published: 25 November 2010
eBook ISBN: 978-0-387-74378-3Published: 24 December 2007
Series ISSN: 0939-6047
Series E-ISSN: 2196-9973
Edition Number: 1
Number of Pages: XII, 276
Number of Illustrations: 130 b/w illustrations
Topics: Image Processing and Computer Vision, Partial Differential Equations, Signal, Image and Speech Processing, Visualization, Applications of Mathematics, Algorithms
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