Overview
- Explains important image processing approach
- Contributes to broader objective, the development of robust efficient fail-safe hybrid intelligent systems
- Valuable for researchers and graduate students in the domains of image processing and computational intelligence
- Includes supplementary material: sn.pub/extras
Part of the book series: Computational Intelligence Methods and Applications (CIMA)
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Table of contents (7 chapters)
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Front Matter
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Back Matter
Keywords
About this book
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 data heterogeneity into the clustering/segmentation procedures.
This is a useful introduction and reference for researchers and graduate students of computer science and electronics engineering, particularly in the domains of image processing and computational intelligence.
Authors and Affiliations
Bibliographic Information
Book Title: Hybrid Soft Computing for Multilevel Image and Data Segmentation
Authors: Sourav De, Siddhartha Bhattacharyya, Susanta Chakraborty, Paramartha Dutta
Series Title: Computational Intelligence Methods and Applications
DOI: https://doi.org/10.1007/978-3-319-47524-0
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer International Publishing AG 2016
Hardcover ISBN: 978-3-319-47523-3Published: 18 November 2016
Softcover ISBN: 978-3-319-83758-1Published: 29 June 2018
eBook ISBN: 978-3-319-47524-0Published: 25 November 2016
Series ISSN: 2510-1765
Series E-ISSN: 2510-1773
Edition Number: 1
Number of Pages: XIV, 235
Number of Illustrations: 60 b/w illustrations, 39 illustrations in colour
Topics: Artificial Intelligence, Computational Intelligence, Computer Imaging, Vision, Pattern Recognition and Graphics