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＜E-Book＞
From Gestalt Theory to Image Analysis : A Probabilistic Approach / by Agnès Desolneux, Lionel Moisan, Jean-Michel Morel
(Interdisciplinary Applied Mathematics. ISSN:21969973 ; 34)

Edition	1st ed. 2008.
Publisher	New York, NY : Springer New York : Imprint: Springer
Year	2008
Language	English
Size	XII, 276 p. 130 illus : online resource
Authors	*Desolneux, Agnès author Moisan, Lionel author Morel, Jean-Michel author SpringerLink (Online service)
Subjects	LCSH:Computer vision LCSH:Differential equations LCSH:Signal processing LCSH:Information visualization LCSH:Mathematics LCSH:Algorithms FREE:Computer Vision FREE:Differential Equations FREE:Signal, Speech and Image Processing FREE:Data and Information Visualization FREE:Applications of Mathematics FREE:Algorithms
Notes	Gestalt Theory -- The Helmholtz Principle -- Estimating the Binomial Tail -- Alignments in Digital Images -- Maximal Meaningfulness and the Exclusion Principle -- Modes of a Histogram -- Vanishing Points -- Contrasted Boundaries -- Variational or Meaningful Boundaries? -- Clusters -- Binocular Grouping -- A Psychophysical Study of the Helmholtz Principle -- Back to the Gestalt Programme -- Other Theories, Discussion 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 HTTP:URL=https://doi.org/10.1007/978-0-387-74378-3

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