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Improving Fingerprint Orientation Extraction

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4 Author(s)
Turroni, F. ; Dept. of Comput. Sci., Univ. of Bologna, Cesena, Italy ; Maltoni, D. ; Cappelli, R. ; Maio, D.

Computation of local orientations is a primary step in fingerprint recognition. A large number of approaches have been proposed in the literature, but no systematic quantitative evaluations have been done yet. We implemented and tested several well know methods and a plethora of their variants over a novel, specifically designed, benchmark, made available in the FVC-onGoing framework. We proved that parameter optimizations, pre- and post-processing stages can markedly improve accuracy of the baseline methods on bad quality fingerprints. Finally, in this paper we propose a novel adaptive method which selectively exploits accuracy of local-based analysis and learning-based global methods, thus achieving the overall best performance on a challenging dataset.

Published in:

Information Forensics and Security, IEEE Transactions on  (Volume:6 ,  Issue: 3 )
Biometrics Compendium, IEEE