Hybrid Soft Computing for Multilevel Image and Data Segmentation
Authors: De, S., Bhattacharyya, S., Chakraborty, S., Dutta, P.
Free Preview- 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
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- About this book
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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.
- Table of contents (7 chapters)
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Introduction
Pages 1-28
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Image Segmentation: A Review
Pages 29-40
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Self-supervised Grey Level Image Segmentation Using an Optimised MUSIG (OptiMUSIG) Activation Function
Pages 41-87
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Self-supervised Colour Image Segmentation Using Parallel OptiMUSIG (ParaOptiMUSIG) Activation Function
Pages 89-123
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Self-supervised Grey Level Image Segmentation Using Multi-Objective-Based Optimised MUSIG (OptiMUSIG) Activation Function
Pages 125-152
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Table of contents (7 chapters)
- Download Preface 1 PDF (54.1 KB)
- Download Sample pages 2 PDF (102.7 KB)
- Download Table of contents PDF (152 KB)
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Bibliographic Information
- Bibliographic Information
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- Book Title
- Hybrid Soft Computing for Multilevel Image and Data Segmentation
- Authors
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- Sourav De
- Siddhartha Bhattacharyya
- Susanta Chakraborty
- Paramartha Dutta
- Series Title
- Computational Intelligence Methods and Applications
- Copyright
- 2016
- Publisher
- Springer International Publishing
- Copyright Holder
- Springer International Publishing AG
- eBook ISBN
- 978-3-319-47524-0
- DOI
- 10.1007/978-3-319-47524-0
- Hardcover ISBN
- 978-3-319-47523-3
- Softcover ISBN
- 978-3-319-83758-1
- Series ISSN
- 2510-1765
- Edition Number
- 1
- Number of Pages
- XIV, 235
- Number of Illustrations
- 60 b/w illustrations, 39 illustrations in colour
- Topics
