On finding appropriate reject region in serial fusion based biometric verification

Abstract

We give the theoretical foundation for finding a reject region which gives the minimum equal error rate in serial fusion based biometric verification. Given a user-specified tolerance of x percent genuine score reject rate, we prove that there exists a unique reject region inside which the false alarm rate and impostor pass rate curves overlap, and this reject region gives the minimum equal error rate. Our theory leads to new algorithms for finding reject regions, which have two key advantages over the state-of-the-art: (1) the algorithms allow the system administrator to control the proportion of genuine scores that a reject region can erroneously reject and (2) the algorithms determine reject regions directly from the scores, without the need to estimate score distributions. Our proofs do not rely on data belonging to any particular distribution, which makes them applicable to a wide range of biometric modalities including face, finger, iris, speech, gait, and keystrokes.