Relating ROC and CMC curves via the biometric menagerie

Brian DeCann, Arun Ross

Abstract: In the academic literature, the matching accuracy of a biometric system is typically quantified through measures such as the Receiver Operating Characteristic (ROC) curve and Cumulative Match Characteristic (CMC) curve. The ROC curve, measuring verification performance, is based on aggregate statistics of match scores corresponding to all biometric samples, while the CMC curve, measuring identification performance, is based on the relative ordering of match scores corresponding to each biometric sample (in closed-set identification). In this study, we determine whether a set of genuine and impostor match scores generated from biometric data can be reassigned to virtual identities, such that the same ROC curve can be accompanied by multiple CMC curves. The reassignment is accomplished by modeling the intra- and inter-class relationships between identities based on the “Doddington Zoo” or “Biometric Menagerie” phenomenon. The outcome of the study suggests that a single ROC curve can be mapped to multiple CMC curves in closed-set identification, and that presentation of a CMC curve should be accompanied by a ROC curve when reporting biometric system performance, in order to better understand the performance of the matcher.