A review of calibration methods for biometric systems in forensic applications


Ali, Tauseef and Spreeuwers, Luuk and Veldhuis, Raymond (2012) A review of calibration methods for biometric systems in forensic applications. In: 33rd WIC Symposium on Information Theory in the Benelux, 24-25 May 2012, Boekelo, the Netherlands.

Abstract:When, in a criminal case there are traces from a crime scene - e.g., finger marks or facial recordings from a surveillance camera - as well as a suspect, the judge has to accept either the hypothesis \emph{$H_{p}$} of the prosecution, stating that the trace originates from the subject, or the hypothesis of the defense \emph{$H_d$}, stating the opposite. The current practice is that forensic experts provide a degree of support for either of the two hypotheses, based on their examinations of the trace and reference data - e.g., fingerprints or photos - taken from the suspect. There is a growing interest in a more objective quantitative support for these hypotheses based on the output of biometric systems instead of manual comparison. However, the output of a score-based biometric system is not directly suitable for quantifying the evidential value contained in a trace. A suitable measure that is gradually becoming accepted in the forensic community is the Likelihood Ratio (LR) which is the ratio of the probability of evidence given \emph{$H_p$} and the probability of evidence given \emph{$H_d$}. In this paper we study and compare different score-to-LR conversion methods (called calibration methods). We include four methods in this comparative study: Kernel Density Estimation (KDE), Logistic Regression (Log Reg), Histogram Binning (HB), and Pool Adjacent Violators (PAV). Useful statistics such as mean and bias of the bootstrap distribution of \emph{LRs} for a single score value are calculated for each method varying population sizes and score location.
Item Type:Conference or Workshop Item
Electrical Engineering, Mathematics and Computer Science (EEMCS)
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