Hybrid Soft Computing for Multilevel Image and Data Segmentation

1. Auflage 2016
ISBN: 978-3-319-47523-3
Verlag: Springer International Publishing

Buch, Englisch, 235 Seiten, HC runder Rücken kaschiert, Format (B × H): 160 mm x 241 mm, Gewicht: 5029 g

Reihe: Computational Intelligence Methods and Applications

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.

Zielgruppe

Research

Autoren/Hrsg.

De, Sourav

Dutta, Paramartha

Bhattacharyya, Siddhartha

Chakraborty, Susanta

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Bildsignalverarbeitung
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Mustererkennung, Biometrik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Fuzzy-Systeme

Inhaltsverzeichnis

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.