White-Box Evaluation of Fingerprint Matchers
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Prevailing evaluations of fingerprint recognition systems have been performed as end-to-end black-box tests of fingerprint identification or verification accuracy. However, performance of the end-to-end system is subject to errors arising in any of the constituent modules, including: fingerprint reader, preprocessing, feature extraction, and matching. While a few studies have conducted white-box testing of the fingerprint reader and feature extraction modules of fingerprint recognition systems, little work has been devoted towards white-box evaluations of the fingerprint matching sub-module. We report results of a controlled, white-box evaluation of one open-source and two commercial-off-the-shelf (COTS) state-of-the-art minutiae-based matchers in terms of their robustness against controlled perturbations (random noise, and non-linear distortions) introduced into the input minutiae feature sets. Experiments were conducted on 10,000 synthetically generated fingerprints. Our white-box evaluations show performance comparisons between different minutiae-based matchers in the presence of various perturbations and non-linear distortion, which were not previously shown with black-box tests. Furthermore, our white-box evaluations reveal that the performance of fingerprint minutiae matchers are more susceptible to non-linear distortion and missing minutiae than spurious minutiae and small positional displacements of the minutiae locations. The measurement uncertainty in fingerprint matching is also developed.
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