Hybrid Soft Computing for Multilevel Image and Data Segmentation

✍ Scribed by Sourav De, Siddhartha Bhattacharyya, Susanta Chakraborty, Paramartha Dutta (auth.)

Publisher: Springer International Publishing
Year: 2016
Tongue: English
Leaves: 245
Series: Computational Intelligence Methods and Applications
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

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

Front Matter....Pages i-xiv
Introduction....Pages 1-28
Image Segmentation: A Review....Pages 29-40
Self-supervised Grey Level Image Segmentation Using an Optimised MUSIG (OptiMUSIG) Activation Function....Pages 41-87
Self-supervised Colour Image Segmentation Using Parallel OptiMUSIG (ParaOptiMUSIG) Activation Function....Pages 89-123
Self-supervised Grey Level Image Segmentation Using Multi-Objective-Based Optimised MUSIG (OptiMUSIG) Activation Function....Pages 125-152
Self-supervised Colour Image Segmentation Using Multiobjective Based Parallel Optimized MUSIG (ParaOptiMUSIG) Activation Function....Pages 153-192
Unsupervised Genetic Algorithm Based Automatic Image Segmentation and Data Clustering Technique Validated by Fuzzy Intercluster Hostility Index....Pages 193-217
Back Matter....Pages 219-235

✦ Subjects

Artificial Intelligence (incl. Robotics);Computational Intelligence;Computer Imaging, Vision, Pattern Recognition and Graphics

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