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Studies of Operational Measurement of ROC Curve on Large Fingerprint Data Sets Using Two-Sample Bootstrap

Published

Author(s)

Jin Chu Wu

Abstract

From the operational perspective, for large-size fingerprint data, a receiver operating characteristic (ROC) curve is usually measured by the true accept rate (TAR) of the genuine scores given a specified false accept rate (FAR) of the impostor scores. The ties of genuine and/or impostor scores at a threshold can often occur for large-size fingerprint data, and how to determine the TAR at an operational FAR is provided. The accuracy of the measurement of TAR at a specified FAR for an ROC curve is explored using the nonparametric two-sample bootstrap. The variability of the estimates of standard error and lower bound and upper bound of 95% confidence interval of two-sample bootstrap distribution of the statistic TARs for large-size fingerprint data is extensively studied empirically. Thereafter, the number of two-sample bootstrap replications is determined. Both high-accuracy and low-accuracy fingerprint-image matching algorithms are taken as examples.
Citation
NIST Interagency/Internal Report (NISTIR) - 7449
Report Number
7449

Keywords

Confidence interval, Fingerprint matching, Nonparametric two-sample bootstrap, Receiver operating characteristic (ROC) Curve, Standard errors, Variability

Citation

, J. (2007), Studies of Operational Measurement of ROC Curve on Large Fingerprint Data Sets Using Two-Sample Bootstrap, NIST Interagency/Internal Report (NISTIR), National Institute of Standards and Technology, Gaithersburg, MD, [online], https://doi.org/10.6028/NIST.IR.7449 (Accessed April 21, 2024)
Created September 4, 2007, Updated November 10, 2018