Fast computation of the performance evaluation of biometric systems: Application to multibiometrics

The performance evaluation of biometric systems is a crucial step when designing and evaluating such systems. The evaluation process uses the Equal Error Rate (EER) metric proposed by the International Organization for Standardization (ISO/IEC). The EER metric is a powerful metric which allows easily comparing and evaluating biometric systems. However, the computation time of the EER is, most of the time, very intensive. In this paper, we propose a fast method which computes an approximated value of the EER. We illustrate the benefit of the proposed method on two applications: the computing of non parametric confidence intervals and the use of genetic algorithms to compute the parameters of fusion functions. Experimental results show the superiority of the proposed EER approximation method in term of computing time, and the interest of its use to reduce the learning of parameters with genetic algorithms. The proposed method opens new perspectives for the development of secure multibiometrics systems by speeding up their computation time.

► We present a very fast way to approximate the EER value of a biometric system. ► This approximation is very close to the real value. ► We present a non parametric parallel confidence interval computing method. ► Two multibiometrics score fusion functions are designed. ► They are configured through genetic algorithm using our EER approximation function.