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Proceedings Paper

Significance test in operational ROC analysis
Author(s): Jin Chu Wu; Alvin F. Martin; Raghu N. Kacker; Charles R. Hagwood
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Paper Abstract

To evaluate the performance of fingerprint-image matching algorithms on large datasets, a receiver operating characteristic (ROC) curve is applied. From the operational perspective, the true accept rate (TAR) of the genuine scores at a specified false accept rate (FAR) of the impostor scores and/or the equal error rate (EER) are often employed. Using the standard errors of these metrics computed using the nonparametric two-sample bootstrap based on our studies of bootstrap variability on large fingerprint datasets, the significance test is performed to determine whether the difference between the performance of one algorithm and a hypothesized value, or the difference between the performances of two algorithms where the correlation is taken into account is statistically significant. In the case that the alternative hypothesis is accepted, the sign of the difference is employed to determine which is better than the other. Examples are provided.

Paper Details

Date Published: 14 April 2010
PDF: 15 pages
Proc. SPIE 7667, Biometric Technology for Human Identification VII, 76670I (14 April 2010); doi: 10.1117/12.849529
Show Author Affiliations
Jin Chu Wu, National Institute of Standards and Technology (United States)
Alvin F. Martin, National Institute of Standards and Technology (United States)
Raghu N. Kacker, National Institute of Standards and Technology (United States)
Charles R. Hagwood, National Institute of Standards and Technology (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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