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Markov Random Field Modeling in Image Analysis

Markov Random Field Modeling in Image Analysis - Advances in Pattern Recognition

3rd Edition

Hardback (02 Apr 2009)

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Publisher's Synopsis

Markov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpretation. It enables us to develop optimal vision algorithms systematically when used with optimization principles. This book presents a comprehensive study on the use of MRFs for solving computer vision problems. Various vision models are presented in a unified framework, including image restoration and reconstruction, edge and region segmentation, texture, stereo and motion, object matching and recognition, and pose estimation. This third edition includes the most recent advances and has new and expanded sections on topics such as: Bayesian Network; Discriminative Random Fields; Strong Random Fields; Spatial-Temporal Models; Learning MRF for Classification. This book is an excellent reference for researchers working in computer vision, image processing, statistical pattern recognition and applications of MRFs. It is also suitable as a text for advanced courses in these areas.

Book information

ISBN: 9781848002784
Publisher: Springer London
Imprint: Springer
Pub date:
Edition: 3rd Edition
DEWEY: 621.36701519233
DEWEY edition: 22
Language: English
Number of pages: 357
Weight: 1570g
Height: 234mm
Width: 156mm
Spine width: 22mm