Independent performance evaluation of fingerprint verification at the minutiae and pseudonymous identifier levels

Often in the development of a biometric product an evaluator of the system is the same entity who developed the algorithm. Moreover, usually the test data employed in such evaluation is also collected by the same developer/evaluator. In most cases such database will not be made public and consequent...

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Veröffentlicht in:2010 IEEE International Conference on Systems, Man and Cybernetics S. 3186 - 3193
Hauptverfasser: Gafurov, D, Bian Yang, Bours, P, Busch, C
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.10.2010
Schlagworte:
Erbium
Magnetic resonance
ISBN:1424465869, 9781424465866
ISSN:1062-922X
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Zusammenfassung:Often in the development of a biometric product an evaluator of the system is the same entity who developed the algorithm. Moreover, usually the test data employed in such evaluation is also collected by the same developer/evaluator. In most cases such database will not be made public and consequently test results cannot be verified by independent institutions. This paper presents an independent report on fingerprint performance evaluation that has been conducted in the context of the TURBINE project. In this study the algorithm developer and system evaluator are represented by separate and independent entities. In addition, the algorithm developer does not have access to the primary test database. All these provide pre-conditions to unbiased and trustworthy performance reports. Furthermore, this paper introduces biometric performance testing on a level of biometric references, which is complementary to image- or minutiae-based references. Biometric references in the TURBINE project are pseudonymous identifiers that have been generated by the template protection algorithms. The results of the performance evaluation in this paper are generated by applying the algorithm developers (binary) algorithms at the minutiae (traditional) and pseudonymous identifier levels. The test data set consists of almost 72000 fingerprint images from 100 subjects acquired by several fingerprint scanners to which the algorithm developers did not have access.
ISBN:1424465869
9781424465866
ISSN:1062-922X
DOI:10.1109/ICSMC.2010.5642276