Automatic Detection of the Optimal Acceptance Threshold in a Face Verification System

Abstract

Abstract. We present a face verification system with an acceptance threshold automatically computed. The user is allowed to provide the rate between the costs assumed for a false acceptance and false rejection. This rate between costs can be intuitively known by the system responsible and are a starting point to fulfil user security requirements. With this user-friendly data, an algorithm based on screening techniques to compute the acceptance threshold is presented in this paper. This algorithm is applied to an original and competitive face verification system based on principal component analysis and two classifiers (neural network radial basis function and support vector machine). Experimental results with a 100 people face database are shown. This method can be also applied into other biometric applications in which this threshold should be calculated.