Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/44364
DC FieldValueLanguage
dc.contributor.authorJuang, C.F.en_US
dc.contributor.author莊家峰zh_TW
dc.contributor.authorChiu, S.H.en_US
dc.contributor.authorShiu, S.J.en_US
dc.date2007zh_TW
dc.date.accessioned2014-06-06T08:12:12Z-
dc.date.available2014-06-06T08:12:12Z-
dc.identifier.issn1083-4427zh_TW
dc.identifier.urihttp://hdl.handle.net/11455/44364-
dc.description.abstractThis paper proposes a Fuzzy System learned through Fuzzy Clustering and Support Vector Machine (FS-FCSVM). The FS-FCSVM is a fuzzy system constructed by fuzzy if-then rules with fuzzy singletons in the consequence. The structure of FS-FCSVM is constructed by fuzzy clustering on the input data, which helps to reduce the number of rules. Parameters in FS-FCSVM are learned through a support vector machine (SVM) for the purpose of achieving higher generalization ability. In contrast to nonlinear kernel-based SVM or some other fuzzy systems with a support vector learning mechanism, both the number of parameters/rules in FS-FCSVM and the computation time are much smaller. FS-FCSVM is applied to skin color segmentation. For color information representation, different types of features based on scaled hue and saturation color space are used. Comparisons with a fuzzy neural network, the Gaussian kernel SVM, and mixture of Gaussian classifiers are performed to show the advantage of FS-FCSVM.en_US
dc.language.isoen_USzh_TW
dc.relationIeee Transactions on Systems Man and Cybernetics Part a-Systems and Humansen_US
dc.relation.ispartofseriesIeee Transactions on Systems Man and Cybernetics Part a-Systems and Humans, Volume 37, Issue 6, Page(s) 1077-1087.en_US
dc.relation.urihttp://dx.doi.org/10.1109/tsmca.2007.904579en_US
dc.subjectcolor segmentationen_US
dc.subjectfuzzy clusteringen_US
dc.subjectfuzzy neural network (FNN)en_US
dc.subjectmixture of Gaussian classifier (MGC)en_US
dc.subjectstructure learningen_US
dc.subjectimage segmentationen_US
dc.subjectnetworksen_US
dc.titleFuzzy system learned through fuzzy clustering and support vector machine for human skin color segmentationen_US
dc.typeJournal Articlezh_TW
dc.identifier.doi10.1109/tsmca.2007.904579zh_TW
item.grantfulltextnone-
item.openairetypeJournal Article-
item.languageiso639-1en_US-
item.fulltextno fulltext-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
Appears in Collections:電機工程學系所
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