A central-limit theorem for a single-false match rate

Zachariah Dietz; Michael E. Schuckers

doi:10.1117/12.849746

14 April 2010 A central-limit theorem for a single-false match rate

Zachariah Dietz, Michael E. Schuckers

Proceedings Volume 7667, Biometric Technology for Human Identification VII; 76670F (2010) https://doi.org/10.1117/12.849746
Event: SPIE Defense, Security, and Sensing, 2010, Orlando, Florida, United States

Abstract

In this paper, we present a central limit theorem (CLT) for the estimation of a false match rate for a single matching system. The false match rate is often a significant factor in an evaluation of such a matching system. To achieve the main result here we utilize the covariance/correlation structure for matching proposed by Schuckers. Along with the main result we present an illustration of the methodology here on biometric authentication data from Ross and Jain. This illustration is from resampling match decisions on three different biometric modalities: hand geometry, fingerprint and facial recognition and shows that as the number of matching pairs grows the sampling distribution for an FMR approaches a Gaussian distribution. These results suggest that statistical inference for a FMR based upon a Gaussian distribution is appropriate.

Citation Download Citation

Zachariah Dietz and Michael E. Schuckers "A central-limit theorem for a single-false match rate", Proc. SPIE 7667, Biometric Technology for Human Identification VII, 76670F (14 April 2010); https://doi.org/10.1117/12.849746

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