Coarse–fine surrogate model driven multiobjective evolutionary fuzzy clustering algorithm with dual memberships for noisy image segmentation

To improve the segmentation performance and boost evolutionary efficiency of multiobjective evolutionary clustering algorithms on noisy images, this paper proposes a coarse–fine surrogate model driven multiobjective evolutionary fuzzy clustering algorithm with dual membership functions (CFS-MOEFC)....

Full description

Bibliographic Details

Published in:	Applied soft computing Vol. 112; p. 107778
Main Authors:	Zhao, Feng, Liu, Feifan, Li, Chaoqi, Liu, Hanqiang, Lan, Rong, Fan, Jiulun
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 01.11.2021
Subjects:	Coarse–fine surrogate model Dual fuzzy memberships Fuzzy clustering Image segmentation Multiobjective evolutionary optimization Image segmentation Coarse–fine surrogate model Fuzzy clustering Dual fuzzy memberships Multiobjective evolutionary optimization
ISSN:	1568-4946, 1872-9681
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!