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Image guided fuzzy clustering for image segmentation
Guo L.; Chen L.; Chen C.L.P.
2017-02-06
Conference NameIEEE International Conference on Systems, Man, and Cybernetics (SMC)
Source Publication2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings
Pages4271-4276
Conference DateOCT 09-12, 2016
Conference PlaceBudapest, HUNGARY
Abstract

Fuzzy clustering methods are efficient tools for image segmentation. However, most of fuzzy clustering approaches are too sensitive to deal with the misclassification of pixels in image segmentation. In recent years, a variety of enhanced fuzzy clustering approaches have been proposed to obtain smoother results in noised image segmentation, but usually with less accurate edges in these results. To fix this problem, we derive some modified algorithms by using Guided Filter, the filter that can reserve the edge information when smoothing every region in segmentation. This paper provides a new roadmap for the application of Guided Filter and gives a thorough discussion of its applications in classical clustering methods, which are Fuzzy C-Means (FCM) and some other variants of FCM. Verified by the experimental results, we conduct a good use of Guided Filter to improve the performance of fuzzy clustering methods in a simple way.

DOI10.1109/SMC.2016.7844902
URLView the original
Indexed BySCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Cybernetics ; Computer Science, Information Systems
WOS IDWOS:000402634704014
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Cited Times [WOS]:2   [WOS Record]     [Related Records in WOS]
Document TypeConference paper
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
AffiliationUniversidade de Macau
Recommended Citation
GB/T 7714
Guo L.,Chen L.,Chen C.L.P.. Image guided fuzzy clustering for image segmentation[C],2017:4271-4276.
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