How to Control Acceptance Threshold for Biometric Signatures with Different Confidence Values?

In the biometric verification, authentication is given when a distance of biometric signatures between enrollment and test phases is less than an acceptance threshold, and the performance is usually evaluated by a so-called Receiver Operating Characteristics (ROC) curve expressing a trade off between False Rejection Rate (FRR) and False Acceptance Rate (FAR). On the other hand, it is also well known that the performance is significantly affected by the situation differences between enrollment and test phases. This paper describes a method to adaptively control an acceptance threshold with quality measures derived from situation differences so as to optimize the ROC curve. We show that the optimal evolution of the adaptive threshold in the domain of the distance and quality measure is equivalent to a constant evolution in the domain of the error gradient defined as a ratio of a total error rate to a total acceptance rate. An experiment with simulation data demonstrates that the proposed method outperforms the previous methods, particularly under a lower FAR or FRR tolerance condition.