Hybrid Soft Computing for Multilevel Image and Data Segmentation
This book explains efficient solutions for segmenting the intensity levels of different types of multilevel images. The authors present hybrid soft computing techniques, which have advantages over conventional soft computing solutions as they incorporate
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Sourav De Siddhartha Bhattacharyya Susanta Chakraborty Paramartha Dutta
Hybrid Soft Computing for Multilevel Image and Data Segmentation
Computational Intelligence Methods and Applications Series editors Sanghamitra Bandyopadhyay, Kolkata, West Bengal, India Ujjwal Maulik, Kolkata, West Bengal, India Patrick Siarry, Vitry-sur-Seine, France
The monographs and textbooks in this series explain methods developed in computational intelligence (including evolutionary computing, neural networks, and fuzzy systems), soft computing, statistics, and artificial intelligence, and their applications in domains such as heuristics and optimization; bioinformatics, computational biology, and biomedical engineering; image and signal processing, VLSI, and embedded system design; network design; process engineering; social networking; and data mining.
More information about this series at http://www.springer.com/series/15197
Sourav De Siddhartha Bhattacharyya Susanta Chakraborty Paramartha Dutta •
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Hybrid Soft Computing for Multilevel Image and Data Segmentation
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Sourav De Department of Computer Science and Engineering Cooch Behar Government Engineering College Cooch Behar, West Bengal India
Susanta Chakraborty Department of Computer Science and Technology Indian Institute of Engineering Science and Technology Howrah, West Bengal India
Siddhartha Bhattacharyya Department of Information Technology RCC Institute of Information Technology Kolkata, West Bengal India
Paramartha Dutta Department of Computer and System Sciences Visva-Bharati University Santiniketan, West Bengal India
ISSN 2510-1765 ISSN 2510-1773 (electronic) Computational Intelligence Methods and Applications ISBN 978-3-319-47523-3 ISBN 978-3-319-47524-0 (eBook) DOI 10.1007/978-3-319-47524-0 Library of Congress Control Number: 2016954909 © Springer International Publishing AG 2016 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, 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. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. Printed on acid-free paper This Springer imprint is published by Springer Nature The regi
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