Estimation and sample size calculations for matching performance of biometric authentication

Performance of biometric authentication devices can be measured in a variety of ways. The most common way is by calculating the false accept and false reject rates, usually referred to as FAR and FRR, respectively. In this paper we present two methodologies for creating confidence intervals for matching error rates. The approach that we take is based on a general parametric model. Because we utilize a parametric model, we are able to ’invert’ our confidence intervals to develop appropriate sample size calculations that account for both number of attempts per person and number of individuals to be tested– a first for biometric authentication testing. The need for sample size calculations that acheive this is currently acute in biometric authentication. These methods are approximate and their small sample performance is assessed through a simulation study. The distribution we use for simulating data is one that arises repeatedly in actual biometric tests.