Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/44451
DC FieldValueLanguage
dc.contributor.authorTaur, J.S.en_US
dc.contributor.author陶金旭zh_TW
dc.contributor.authorLee, G.H.en_US
dc.contributor.authorTao, C.W.en_US
dc.contributor.authorChen, C.C.en_US
dc.contributor.authorYang, C.W.en_US
dc.date2006zh_TW
dc.date.accessioned2014-06-06T08:12:18Z-
dc.date.available2014-06-06T08:12:18Z-
dc.identifier.issn1083-4419zh_TW
dc.identifier.urihttp://hdl.handle.net/11455/44451-
dc.description.abstractIn this paper, a method is proposed for the segmentation of color images using a multiresolution-based signature subspace classifier (MSSC) with application to psoriasis images. The essential techniques consist of feature extraction and image segmentation (classification) methods. In this approach, the fuzzy texture spectrum and the two-dimensional fuzzy color histogram in the hue-saturation space are first adopted as the feature vector to locate homogeneous regions in the image. Then these regions are used to compute the signature matrices for the orthogonal subspace classifier to obtain a more accurate segmentation. To reduce the computational requirement, the MSSC has been developed. In the experiments, the method is quantitatively evaluated by using a similarity function and compared with the well-known LS-SVM method. The results show that the proposed algorithm can effectively segment psoriasis images. The proposed approach can also be applied to general color texture segmentation applications.en_US
dc.language.isoen_USzh_TW
dc.relationIeee Transactions on Systems Man and Cybernetics Part B-Cyberneticsen_US
dc.relation.ispartofseriesIeee Transactions on Systems Man and Cybernetics Part B-Cybernetics, Volume 36, Issue 2, Page(s) 390-402.en_US
dc.relation.urihttp://dx.doi.org/10.1109/tsmcb.2005.859935en_US
dc.subjectfuzzy texture spectrumen_US
dc.subjectimage segmentationen_US
dc.subjectsignature subspaceen_US
dc.subjectclassifieren_US
dc.subjectvector machine classifiersen_US
dc.subjectprojection approachen_US
dc.subjecttexture classificationen_US
dc.subjectneural-networksen_US
dc.subjectregionen_US
dc.subjectinformationen_US
dc.subjectextractionen_US
dc.subjecthistogramen_US
dc.titleSegmentation of psoriasis vulgaris images using multiresolution-based orthogonal subspace techniquesen_US
dc.typeJournal Articlezh_TW
dc.identifier.doi10.1109/tsmcb.2005.859935zh_TW
item.cerifentitytypePublications-
item.grantfulltextnone-
item.languageiso639-1en_US-
item.fulltextno fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.openairetypeJournal Article-
Appears in Collections:電機工程學系所
Show simple item record
 

Google ScholarTM

Check

Altmetric

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.