A change in classification error rates for a biometric device is often referred to as template aging. Here we offer two methods for determining whether the effect of time is statistically significant. The first of these is the use of a generalized linear model to determine if these error rates change linearly over time. This approach generalizes previous work assessing the impact of covariates using generalized linear models. The second approach uses of likelihood ratio tests methodology. The focus here is on statistical methods for estimation not the underlying cause of the change in error rates over time. These methodologies are applied to data from the National Institutes of Standards and Technology Biometric Score Set Release 1. The results of these applications are discussed.

Date Published: 17 April 2006
PDF: 7 pages
Proc. SPIE 6202, Biometric Technology for Human Identification III, 62020M (17 April 2006); doi: 10.1117/12.666417

Published in SPIE Proceedings Vol. 6202:
Biometric Technology for Human Identification III
Patrick J. Flynn; Sharath Pankanti, Editor(s)