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1、MethodofFaceRecognitionBasedonRed-BlackWaveletTransformandPCAYuqingHe,HuanHe,andHongyingYangDepartmentofOpto-ElectronicEngineering,BeijingInstituteofTechnology,Beijing,P.R.China,10008120701170@bit.edu.cnAbstract.Withthedevelopmentoftheman-machineinterfaceandtherecogni-
2、tiontechnology,facerecognitionhasbecameoneofthemostimportantresearchaspectsinthebiologicalfeaturesrecognitiondomain.Nowadays,PCA(PrincipalComponentsAnalysis)hasappliedinrecognitionbasedonmanyfacedatabaseandachievedgoodresults.However,PCAhasitslimitations:thelargevolume
3、ofcomputingandthelowdistinctionability.Inviewoftheselimitations,thispaperputsforwardafacerecognitionmethodbasedonred-blackwavelettransformandPCA.Theimprovedhistogramequalizationisusedtorealizeimagepre-processinginordertocompensatetheillumination.Then,applingthered-blac
4、kwaveletsub-bandwhichcontainstheinformationoftheoriginalimagetoextractthefeatureanddomatching.Comparingwiththetraditionalmethods,thisonehasbetterrecognitionrateandcanreducethecomputationalcomplexity.Keywords:Red-blackwavelettransform,PCA,Facerecognition,Improvedhistogr
5、amequalization.1IntroductionBecausethetraditionalstatusrecognition(IDcard,password,etc)hassomedefects,therecognitiontechnologybasedonbiologicalfeatureshasbecomethefocusofthere-search.Comparedwiththeotherbiologicalfeatures(suchasfingerprints,DNA,palmprints,etc)recogniti
6、ontechnology,peopleidentifywiththepeoplearoundmostlyusingthebiologicalcharacteristicsofhumanface.Faceisthemostuniversalmodeinhumanvision.Thevisualinformationreflectedbyhumanfaceintheexchangeandcontactofpeoplehasanimportantroleandsignificance.Therefore,facerecognitionis
7、theeasiestwaytobeacceptedintheidentificationfieldandbecomesoneofmostpotentialiden-tificationauthenticationmethods.Facerecognitiontechnologyhasthecharacteristicsofconvenientaccess,richinformation.Ithaswiderangeofapplicationssuchasiden-tification,driver'slicenseandpasspo
8、rtcheck,bankingandcustomscontrolsystem,andotherfields[1].Themainmethodsoffacerecognitiontechnologycanbesummeduptothre