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Hybrid soft computing for image segm...

Bhattacharyya, Siddhartha.

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Hybrid soft computing for image segmentation

Record Type:	Electronic resources : Monograph/item
Title/Author:	Hybrid soft computing for image segmentation/ edited by Siddhartha Bhattacharyya ... [et al.].
other author:	Bhattacharyya, Siddhartha.
Published:	Cham :Springer International Publishing : : 2016.,
Description:	xvi, 321 p. :ill., digital ;24 cm.
[NT 15003449]:	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.
Contained By:	Springer eBooks
Subject:	Image segmentation. -
Online resource:	http://dx.doi.org/10.1007/978-3-319-47223-2
ISBN:	9783319472232

Hybrid soft computing for image segmentation
Hybrid soft computing for image segmentation[electronic resource] /edited by Siddhartha Bhattacharyya ... [et al.]. - Cham :Springer International Publishing :2016. - xvi, 321 p. :ill., digital ;24 cm.

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.

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.

ISBN: 9783319472232

Standard No.: 10.1007/978-3-319-47223-2doiSubjects--Topical Terms:

2132796
Image segmentation.

LC Class. No.: TA1632 / .H93 2016

Dewey Class. No.: 006.6

Hybrid soft computing for image segmentation
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245 0 0 $a Hybrid soft computing for image segmentation $h [electronic resource] / $c edited by Siddhartha Bhattacharyya ... [et al.].
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2016.
300 $a xvi, 321 p. : $b ill., digital ; $c 24 cm.
505 0 $a 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.
520 $a 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.
650 0 $a Image segmentation. $3 2132796
650 0 $a Soft computing. $3 563033
650 1 4 $a Computer Science. $3 626642
650 2 4 $a Artificial Intelligence (incl. Robotics) $3 890894
650 2 4 $a Computational Intelligence. $3 1001631
650 2 4 $a Computer Imaging, Vision, Pattern Recognition and Graphics. $3 890871
700 1 $a Bhattacharyya, Siddhartha. $3 2179171
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-47223-2
950 $a Computer Science (Springer-11645)