國立虎尾科技大學 |

Hybrid soft computing for image segmentation

Record Type:	Language materials, printed : 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.;
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:

1062552
Image segmentation.

LC Class. No.: TA1632 / .H93 2016

Dewey Class. No.: 006.6

Hybrid soft computing for image segmentation
LDR:02251nam a2200325 a 4500 001 868049
003 DE-He213
005 20161112170425.0
006 m d
007 cr nn 008maaau
008 170720s2016 gw s 0 eng d
020 $a 9783319472232 $q (electronic bk.)
020 $a 9783319472225 $q (paper)
024 7 $a 10.1007/978-3-319-47223-2 $2 doi
035 $a 978-3-319-47223-2
040 $a GP $c GP
041 0 $a eng
050 4 $a TA1632 $b .H93 2016
072 7 $a UYQ $2 bicssc
072 7 $a TJFM1 $2 bicssc
072 7 $a COM004000 $2 bisacsh
082 0 4 $a 006.6 $2 23
090 $a TA1632 $b .H992 2016
245 0 0 $a Hybrid soft computing for image segmentation $h [electronic resource] / $c edited by Siddhartha Bhattacharyya ... [et al.].
260 $a Cham : $c 2016. $b Springer International Publishing : $b Imprint: Springer,
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 1062552
650 0 $a Soft computing. $3 562548
650 1 4 $a Computer Science. $3 593922
650 2 4 $a Artificial Intelligence (incl. Robotics) $3 593924
650 2 4 $a Computational Intelligence. $3 768837
650 2 4 $a Computer Imaging, Vision, Pattern Recognition and Graphics. $3 671334
700 1 $a Bhattacharyya, Siddhartha. $3 1078852
710 2 $a SpringerLink (Online service) $3 593884
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)