Markov random field for images

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Advances in Pattern Recognition

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Stan Z. Li

Markov Random Field
Modeling in Image Analysis
Third Edition


Stan Z. Li
Center for Biometrics and Security Research &
National Laboratory of Pattern Recognition
Institute of Automation
Chinese Academy of Science
Beijing 100190, China

Series editor
Professor Sameer Singh, PhD
Research School of Informatics, Loughborough University, Loughborough, UK

ISBN: 978-1-84800-278-4
e-ISBN: 978-1-84800-279-1
DOI: 10.1007/978-1-84800-279-1
Advances in Pattern Recognition Series ISSN 1617-7916
British Library Cataloguing in Publication Data
A catalogue record for this book is available from the British Library
Library of Congress Control Number: 2008943235
c Springer-Verlag London Limited 2009
Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act 1988, this publication may only be reproduced,
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the publishers.
The use of registered names, trademarks, etc. in this publication does not imply, even in the absence of a
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for general use.
The publisher makes no representation, express or implied, with regard to the accuracy of the information
contained in this book and cannot accept any legal responsibility or liability for any errors or omissions
that may be made.
Printed on acid-free paper
Springer Science+Business Media

In Memory of My Mother


“An excellent book — very thorough and very clearly written.”
— Stuart Geman

“I have found the book to be a very valuable reference. I am very
impressed by both the breadth and depth of the coverage. This
must have been a truly monumental undertaking.”
— Charles A. Bouman


Foreword by Anil K. Jain
The objective of mathematical modeling in image processing and computer
vision is to capture the intrinsic character of the image in a few parameters so as to understand the nature of the phenomena generating the image.
Models are also useful to specify ...
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