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Proceedings Paper

A central-limit theorem for a single-false match rate
Author(s): Zachariah Dietz; Michael E. Schuckers
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Paper 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.

Paper Details

Date Published: 14 April 2010
PDF: 9 pages
Proc. SPIE 7667, Biometric Technology for Human Identification VII, 76670F (14 April 2010); doi: 10.1117/12.849746
Show Author Affiliations
Zachariah Dietz, Hamilton College (United States)
Michael E. Schuckers, St. Lawrence Univ. (United States)


Published in SPIE Proceedings Vol. 7667:
Biometric Technology for Human Identification VII
B. V. K. Vijaya Kumar; Salil Prabhakar; Arun A. Ross, Editor(s)

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