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New shadowed fuzzy C-means algorithm for image segmentation
Chen L.; Chen S.
2016-10-07
Conference Name3rd International Conference on Informative and Cybernetics for Computational Social Systems (ICCSS)
Source Publication2016 3rd International Conference on Informative and Cybernetics for Computational Social Systems, ICCSS 2016
Pages43-46
Conference DateAUG 26-29, 2016
Conference PlaceJinzhou, PEOPLES R CHINA
Abstract

This manuscript introduces a new clustering based image segmentation method. By implanting the concept of shadowed set in the estimation procedure for cluster centers, one new algorithm named shadowed modified C-mean algorithm (SMFCM) is proposed. The results on noise image segmentation demonstrate the shadowed modified fuzzy C-mean is better than some traditional approaches when the noise rate is high.

KeywordFuzzy Clustering Image Segmentation Shadowed Set
DOI10.1109/ICCSS.2016.7586420
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Cybernetics ; Engineering, Electrical & Electronic
WOS IDWOS:000390239500009
Scopus ID2-s2.0-84994387585
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Citation statistics
Document TypeConference paper
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
AffiliationUniversidade de Macau
First Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Chen L.,Chen S.. New shadowed fuzzy C-means algorithm for image segmentation[C], 2016, 43-46.
APA Chen L.., & Chen S. (2016). New shadowed fuzzy C-means algorithm for image segmentation. 2016 3rd International Conference on Informative and Cybernetics for Computational Social Systems, ICCSS 2016, 43-46.
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