Abstract
False match rates are an important measure of bioauthentication system performance. The false match rate (FMR) is the rate at which a biometric process mismatches biometric signals from two distinct individuals as coming from the same individual. Statistical methods for that rate are the focus of this chapter. We begin with an introduction to false match rates and the notation that we’ll use throughout this chapter. That is followed by a section on the correlation structure for the two-instance false match rate. In that section, we also discuss estimation of parameters in the general correlation structure as well as some simplifications of that general correlation structure. Section 4.2 contains a description of the two-instance bootstrap for estimation on an FNMR. The two-instance bootstrap is a new methodology for estimation of the sampling variability in an FNMR. We then turn to statistical methods for a single FNMR as well as for multiple FNMR’s. Large sample as well as bootstrap and randomization approaches to confidence intervals and hypothesis tests are given. This is followed by a section on sample size and power calculations for an FNMR. Prediction intervals for the FNMR are the focus on the next section. Lastly, we provide a brief discussion of the statistical methods for the FNMR in this chapters.
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Schuckers, M.E. (2010). False Match Rate. In: Computational Methods in Biometric Authentication. Information Science and Statistics. Springer, London. https://doi.org/10.1007/978-1-84996-202-5_4
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DOI: https://doi.org/10.1007/978-1-84996-202-5_4
Publisher Name: Springer, London
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