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Siddhartha Bhattacharyya & Paramartha Dutta 
Hybrid Soft Computing for Image Segmentation 

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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.

€96.29
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Table of Content

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. 

Language English ● Format PDF ● Pages 321 ● ISBN 9783319472232 ● File size 16.9 MB ● Editor Siddhartha Bhattacharyya & Paramartha Dutta ● Publisher Springer International Publishing ● City Cham ● Country CH ● Published 2016 ● Downloadable 24 months ● Currency EUR ● ID 5011424 ● Copy protection Social DRM

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