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