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From Gestalt Theory to Image Analysis - A Probabilistic Approach (Hardcover, 2008 ed.): Agnes Desolneux, Lionel Moisan,... From Gestalt Theory to Image Analysis - A Probabilistic Approach (Hardcover, 2008 ed.)
Agnes Desolneux, Lionel Moisan, Jean-Michel Morel
R1,550 Discovery Miles 15 500 Ships in 10 - 15 working days

This book introduces a new theory in Computer Vision yielding elementary techniques to analyze digital images. These techniques are a mathematical formalization of the Gestalt theory. 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 mathematically self-contained, needing only basic understanding of probability and calculus. The text includes more than 130 illustrations, and numerous examples based on specific images on which the theory is tested. Detailed exercises at the end of each chapter help the reader develop a firm understanding of the concepts imparted.

From Gestalt Theory to Image Analysis - A Probabilistic Approach (Paperback, Softcover reprint of hardcover 1st ed. 2008):... From Gestalt Theory to Image Analysis - A Probabilistic Approach (Paperback, Softcover reprint of hardcover 1st ed. 2008)
Agnes Desolneux, Lionel Moisan, Jean-Michel Morel
R1,519 Discovery Miles 15 190 Ships in 10 - 15 working days

This book introduces a new theory in Computer Vision yielding elementary techniques to analyze digital images. These techniques are a mathematical formalization of the Gestalt theory. 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 mathematically self-contained, needing only basic understanding of probability and calculus. The text includes more than 130 illustrations, and numerous examples based on specific images on which the theory is tested. Detailed exercises at the end of each chapter help the reader develop a firm understanding of the concepts imparted.

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