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1、IEEETRANSACTIONSONPATTERNANALYSISANDMACHINEINTELLIGENCE,VOL.33,NO.5,MAY2011945Multifeature-BasedHigh-ResolutionPalmprintRecognitionJifengDaiandJieZhou,SeniorMember,IEEEAbstract—Palmprintisapromisingbiometricfeatureforuseinaccesscontrolandforensicapplications.Previousresearchonpalmprintrecogn
2、itionmainlyconcentratesonlow-resolution(about100ppi)palmprints.Butforhigh-securityapplications(e.g.,forensicusage),high-resolutionpalmprints(500ppiorhigher)arerequiredfromwhichmoreusefulinformationcanbeextracted.Inthispaper,weproposeanovelrecognitionalgorithmforhigh-resolutionpalmprint.Thema
3、incontributionsoftheproposedalgorithmincludethefollowing:1)useofmultiplefeatures,namely,minutiae,density,orientation,andprincipallines,forpalmprintrecognitiontosignificantlyimprovethematchingperformanceoftheconventionalalgorithm.2)Designofaquality-basedandadaptiveorientationfieldestimational
4、gorithmwhichperformsbetterthantheexistingalgorithmincaseofregionswithalargenumberofcreases.3)Useofanovelfusionschemeforanidentificationapplicationwhichperformsbetterthanconventionalfusionmethods,e.g.,weightedsumrule,SVMs,orNeyman-Pearsonrule.Besides,weanalyzethediscriminativepowerofdifferent
5、featurecombinationsandfindthatdensityisveryusefulforpalmprintrecognition.Experimentalresultsonthedatabasecontaining14,576fullpalmprintsshowthattheproposedalgorithmhasachievedagoodperformance.Inthecaseofverification,therecognitionsystem’sFalseRejectionRate(FRR)is16percent,whichis17percentlowe
6、rthanthebestexistingalgorithmataFalseAcceptanceRate(FAR)of105,whileintheidentificationexperiment,therank-1live-scanpartialpalmprintrecognitionrateisimprovedfrom82.0to91.7percent.IndexTerms—Palmprint,orientationfield,thecompositealgorithm,densitymap,datafusion.Ç1INTRODUCTIONPALMPRINTrecognit
7、ionhasconsiderablepotentialasathreeregions:thenar,hypothenar,andinterdigital.Mutablepersonalidentificationtechnique.Palmprintssharecreasesmainlycomefromdryingcracks,whichcomeintomostofthediscriminativefeatureswithfingerprintsand,beinginSpringandWin
