{"title":"Using Biometric Verification to Estimate Identification Performance","authors":"J. Hube","doi":"10.1109/BCC.2006.4341620","DOIUrl":null,"url":null,"abstract":"We show how to estimate identification performance for arbitrary gallery size from an ROC curve. The method presented can: (1) estimate an alarm curve; (2) give rank 1 dependence on gallery size; and (3) estimate a CMC curve. We show that the method assumes consistently normalized scores, with normalization the degree of freedom defining the connection between identification and verification. A measure to quantify normalization consistency is defined. Examples are given using both fingerprint and face databases. Further examples are based on the results given in the FRVT 2002 evaluation report.","PeriodicalId":226152,"journal":{"name":"2006 Biometrics Symposium: Special Session on Research at the Biometric Consortium Conference","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 Biometrics Symposium: Special Session on Research at the Biometric Consortium Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BCC.2006.4341620","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12
Abstract
We show how to estimate identification performance for arbitrary gallery size from an ROC curve. The method presented can: (1) estimate an alarm curve; (2) give rank 1 dependence on gallery size; and (3) estimate a CMC curve. We show that the method assumes consistently normalized scores, with normalization the degree of freedom defining the connection between identification and verification. A measure to quantify normalization consistency is defined. Examples are given using both fingerprint and face databases. Further examples are based on the results given in the FRVT 2002 evaluation report.
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