Multi-order biometric score analysis framework and its application to designing and evaluating biometric systems for access and border control

Traditionally, automated access and border control biometric systems are thought of and designed as verification 1-to-1 systems, where a single comparison between a probe and the claimed identity is examined to allow or disallow the entry to a person; and as such they have been evaluated to date - by using the error tradeoff statistics, which counts how many times a person was falsely accepted or rejected. Such a design however may soon become obsolete due to the recent shift towards applying biometrics to free-flow surveillance-like environments and also in the light of recent findings showing that performance of many verification systems can be improved through the use of several 1-to-N scores, instead of relying on a single 1-to-1 score only. As the framework for designing biometric-enabled access and border control systems changes, so has to change the methodology for the evaluation of such systems. This paper addresses this problem by establishing the multi-order biometric score analysis framework. The framework incorporates latest innovations and recommendations related to the comprehensive evaluation of biometric systems, including subject-based analysis, calibrated score analysis, and two new performance metrics: threshold-validated recognition ranking and non-confident decisions due to multiple threshold-validated scores. The framework is implemented in the Comprehensive Biometrics Evaluation Toolkit (C-BET) and has been applied for the evaluation of several biometric modalities, in particular, those that are frequently contemplated for the use in unconstrained access-border control applications, such as face, voice and iris. The results of the iris modality evaluation are presented in this paper.