Applications of Pulse-Coupled Neural Networks
"Applications of Pulse-Coupled Neural Networks" explores the fields of image processing, including image filtering, image segmentation, image fusion, image coding, image retrieval, and biometric recognition, and the role of pulse-coupled neural networks i
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Yide Ma Kun Zhan Zhaobin Wang
Applications of Pulse-Coupled Neural Networks
With 161 Figures
Authors Yide Ma
Kun Zhan
School of Information Science and
School of Information Science and
Engineering
Engineering
Lanzhou University
Lanzhou University
Gansu 730000, P. R. China
Gansu 730000, P. R. China
E-mail: [email protected]
E-mail: [email protected]
Zhaobin Wang School of Information Science and Engineering Lanzhou University Gansu 730000, P. R. China E-mail: [email protected]
ISBN 978-7-04-027978-8 Higher Education Press, Beijing ISBN 978-3-642-13744-0
e-ISBN 978-3-642-13745-7
Springer Heidelberg Dordrecht London New York Library of Congress Control Number: 2010928904 c Higher Education Press, Beijing and Springer-Verlag Berlin Heidelberg 2010 This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilm or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer-Verlag. Violations are liable to prosecution under the German Copyright Law. The use of general descriptive names, registered names, trademarks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. Cover design: Frido Steinen-Broo, EStudio Calamar, Spain Printed on acid-free paper Springer is part of Springer Science + Business Media (www.springer.com)
Preface
There is no more complicated, advantaged and powerful device than the mammalian primate cortical visual system for image processing in nature. The pulse-coupled neural network (PCNN) is inspired from the investigation of pulse synchronization within the mammalian visual cortex, and has been widely applied to image processing and pattern recognition. Visual cortex is the passage for brain to acquire information from eyes and a part of brain central nervous system. Several biological models based on visual cortex were proposed through investigation of cat cortex and had been applied to image processing. The PCNN emulates the mammalian visual cortex, which is supposed to be one of the most efficient image processing methods. The output of the PCNN is a series of pulse images which represent the fundamental features of original stimulus, such as edge, texture, and segment. Neurons receive inputs from other neurons through synapses and are fired synchronously in certain regions, that is why the PCNN can be applied to image segmentation, smoothing, and coding. Another important feature of the PCNN is that the pulse images are able to be characterized to a unique invariant signature for the image retrieval. This book analyzes the PCNN in detail and presents
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