Agnès Desolneux – författare

This richly illustrated book introduces the reader to a newly developed theory in Computer Vision yielding elementary techniques to analyze digital images. These techniques are inspired by, and are a mathematical formalization of the Gestalt theory. The authors maintain a publicly available software program called MegaWave, containing implementations of most of the image analysis techniques developed in the book. The volume is intended for a multidisciplinary audience of researchers and engineers. It is mathematically self-contained and requires only the basic understanding of probability and calculus. The text contains more than 130 illustrations. The authors offer 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.

This richly illustrated book introduces the reader to a newly developed theory in Computer Vision yielding elementary techniques to analyze digital images. These techniques are inspired by, and are a mathematical formalization of the Gestalt theory. The authors maintain a publicly available software program called MegaWave, containing implementations of most of the image analysis techniques developed in the book. The volume is intended for a multidisciplinary audience of researchers and engineers. It is mathematically self-contained and requires only the basic understanding of probability and calculus. The text contains more than 130 illustrations. The authors offer 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.

Pattern theory is a distinctive approach to the analysis of all forms of real-world signals. At its core is the design of a large variety of probabilistic models whose samples reproduce the look and feel of the real signals, their patterns, and their variability. Bayesian statistical inference then allows you to apply these models in the analysis of new signals. This book treats the mathematical tools, the models themselves, and the computational algorithms for applying statistics to analyze six representative classes of signals of increasing complexity. The book covers patterns in text, sound, and images. Discussions of images include recognizing characters, textures, nature scenes, and human faces. The text includes online access to the materials (data, code, etc.) needed for the exercises.

Pattern theory is a distinctive approach to the analysis of all forms of real-world signals. At its core is the design of a large variety of probabilistic models whose samples reproduce the look and feel of the real signals, their patterns, and their variability. Bayesian statistical inference then allows you to apply these models in the analysis of new signals. This book treats the mathematical tools, the models themselves, and the computational algorithms for applying statistics to analyze six representative classes of signals of increasing complexity. The book covers patterns in text, sound, and images. Discussions of images include recognizing characters, textures, nature scenes, and human faces. The text includes onlineaccess to thematerials (data, code, etc.) needed for the exercises.

Pattern theory is a distinctive approach to the analysis of all forms of real-world signals. At its core is the design of a large variety of probabilistic models whose samples reproduce the look and feel of the real signals, their patterns, and their variability. Bayesian statistical inference then allows you to apply these models in the analysis of new signals. This book treats the mathematical tools, the models themselves, and the computational algorithms for applying statistics to analyze six representative classes of signals of increasing complexity. The book covers patterns in text, sound, and images. Discussions of images include recognizing characters, textures, nature scenes, and human faces. The text includes onlineaccess to thematerials (data, code, etc.) needed for the exercises.

This richly illustrated book introduces the reader to a newly developed theory in Computer Vision yielding elementary techniques to analyze digital images. These techniques are inspired by, and are a mathematical formalization of the Gestalt theory. The authors maintain a publicly available software program called MegaWave, containing implementations of most of the image analysis techniques developed in the book. The volume is intended for a multidisciplinary audience of researchers and engineers. It is mathematically self-contained and requires only the basic understanding of probability and calculus. The text contains more than 130 illustrations. The authors offer 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.