Siddhartha Bhattacharyya & Paramartha Dutta 
Hybrid Soft Computing for Image Segmentation 

Support

This book proposes soft computing techniques for segmenting real-life images in applications such as image processing, image mining, video surveillance, and intelligent transportation systems. The book suggests hybrids deriving from three main approaches: fuzzy systems, primarily used for handling real-life problems that involve uncertainty; artificial neural networks, usually applied for machine cognition, learning, and recognition; and evolutionary computation, mainly used for search, exploration, efficient exploitation of contextual information, and optimization.


The contributed chapters discuss both the strengths and the weaknesses of the approaches, and the book will be valuable for researchers and graduate students in the domains of image processing and computational intelligence.

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Table des matières

Hybrid Soft Computing Techniques for Image Segmentation: Fundamentals and Applications.- Enhanced Rough-Fuzzy C-Means Algorithm for Image Segmentation.- Intuitionistic Fuzzy C-means Clustering Algorithm for Brain Image Segmentation.- Automatic Segmentation Approaches.- Modified Level Set Segmentation.- Fuzzy Deformable Models for 3D Segmentation of Brain Structures.- Rough Sets for Probabilistic Model Based Image Segmentation.- Segmentation of Cerebral Images. 

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Langue Anglais ● Format PDF ● Pages 321 ● ISBN 9783319472232 ● Taille du fichier 16.9 MB ● Éditeur Siddhartha Bhattacharyya & Paramartha Dutta ● Maison d’édition Springer International Publishing ● Lieu Cham ● Pays CH ● Publié 2016 ● Téléchargeable 24 mois ● Devise EUR ● ID 5011424 ● Protection contre la copie DRM sociale

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