Optimization of Thresholds in Serial Multimodal Biometric Systems

Abstract

Multimodal biometric verification systems use information from several biometric modalities to verify an identity of a person. The false acceptance rate (FAR) and false rejection rate (FRR) are metrics generally used to measure the performance of such systems. In this paper we propose a novel approach to determine the upper and lower acceptance thresholds in sequential multimodal biometric matching, in such a way that the expected values of FAR and FRR for the entire system are minimized. We linearize locally the score distributions of both genuine users and impostors using the least squares method, and derive formulas for the approximated FAR and FRR for each matcher. Further, we aim to minimize both probabilities for entire processing chain. In order to find the best compromise between them, we analyze the efficient solutions to the associated bi-objective programming problem. The results of our experiments are also reported in the paper. They showed a good performance of the sequential multiple biometric matching system based on optimized thresholds comparing with the widely adopted parallel fusion multimodal biometric systems.