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1、ANIMAGERETRIEVALTECHNIQUEUSINGROTATIONALLYINVARIANTGABORFEATURESANDALOCALIZATIONMETHODDaekyuShin,DaewonKim,HyunsoolKim,*SanghiParkSamsungElectronicsCo.Ltd.Paldal-Gu,Maetan3dong,416,Suwon,Korea,442-742Phone:+82.31.279.5593,5269,6739Fax:+82.31.279.5515E-mail:daekymshin,drdw.kim,h~in
2、sool.kim~samsune.com*DepartmentofElectricalandElectronicsEngineering*YonseiUniversity*134Sinchon-dong,Seodaemun-gu,Seoul120-749,Korea*E-mail:psh@cyber.yonsei.ac.krABSTRACTmulti-resolutionfilteringtechniquebasedonGaborwaveletfiltersfortextureanalysishasbeenshowntobeInordertosearchi
3、magesinadatabase,acontentbasedoptimalinthesenseofminimizingthejointtwo-imageretrievalmethodsarewidelyusedforfindingdimensionaluncertaintyinspaceandfrequency.However,visuallysimilaronetoagivensampleimage.ThetheGaborfilterbankhasbecomegenerallyknownnottoapproachesusingGaborfunctions
4、andfiltersareregardedberobust[2]especiallyforrotatedimagesandthat’stheasoneoftheexcellentmethodsforfeatureextractionandobjectiveofresearchproposedinthispaper.Therotationtexturesegmentations.However,theGabormethoddoesinvariantGaborfilterispresentedandnotperformwellspecificallyforar
5、otatedimagesincetheVQandhistogrammethodsareusedforsearchingimages.filterhasadirectionorientedproperty.ThispaperThefeaturevectorsareclassifiedbyVQandformaproposesamethodofextractinglocaltexturefeatureshistogramofconstructedcodebookindex.lmageretrievalsfiomblockswithcentralinterestp
6、ointsextractedfromanareperformedbycomparisonoffeaturesbetweenimagesimageandarotationallyinvariantGaborwaveletfilter.Aindatabaseandthequeryimage.Performanceofthemethodofcomparisonamongthepattemhistogramsthatproposedalgorithmisevaluatedthroughanapplicationofareconstructedfeaturesare
7、presentedaftertheimageswitharotation,asmallscalechange,noiseclassificationusingvectorquantization(VQ)betweenaddition,andpartialsection.images.2.FEATUREEXTRACTION1.INTRODUCTIONManyresearchershaveusedtheglobalfeaturesofanThroughtherecentemergenceofintemet,itbecomesimagefortheimagere
8、trieval.Theapproachcannotpossible
