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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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.
Imprint | Springer-Verlag New York |
Country of origin | United States |
Series | Interdisciplinary Applied Mathematics, 34 |
Release date | November 2010 |
Availability | Expected to ship within 10 - 15 working days |
First published | 2008 |
Authors | Agnes Desolneux, Lionel Moisan, Jean-Michel Morel |
Dimensions | 235 x 155 x 15mm (L x W x T) |
Format | Paperback |
Pages | 276 |
Edition | Softcover reprint of hardcover 1st ed. 2008 |
ISBN-13 | 978-1-4419-2481-0 |
Barcode | 9781441924810 |
Categories | |
LSN | 1-4419-2481-7 |