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 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.

List of contents

Introduction.- Image Segmentation: A Review.- Self-supervised Gray Level Image Segmentation Using an Optimized MUSIG (OptiMUSIG) Activation Function.- Self-supervised Color Image Segmentation Using Parallel OptiMUSIG (ParaOptiMUSIG) Activation Function.- Self-supervised Gray Level Image Segmentation Using Multiobjective Based Optimized MUSIG (OptiMUSIG) Activation Function.- Self-supervised Color Image Segmentation Using Multiobjective Based Parallel Optimized MUSIG (ParaOptiMUSIG) Activation Function.- Unsupervised Genetic Algorithm Based Automatic Image Segmentation and Data Clustering Technique Validated by Fuzzy Intercluster Hostility Index.

Summary

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.

Product details

• Authors: Siddharth Bhattacharyya, Siddhartha Bhattacharyya, Chakraborty, Susanta Chakraborty, Soura De, Sourav De, Paramartha Dutta
• Publisher: Springer, Berlin
• Languages: English
• Product format: Hardback
• Released: 01.01.2016
• EAN: 9783319475233
• ISBN: 978-3-31-947523-3
• No. of pages: 235
• Dimensions: 169 mm x 242 mm x 20 mm
• Weight: 491 g
• Illustrations: XIV, 235 p. 99 illus., 39 illus. in color.
• Series: Computational Intelligence Methods and Applications; Computational Intelligence Methods and Applications
• Subjects: Natural sciences, medicine, IT, technology > IT, data processing > IT; B, Artificial Intelligence, Bildverarbeitung, computer science, Computer Vision, Computer Imaging, Vision, Pattern Recognition and Graphics, Computational Intelligence, Optical data processing, Image processing