The use of a wavelet-Markov local descriptor, which exploits joint dependencies among wavelet coefficients, for fingerprint liveness detection, is proposed. On the LivDet 2009 datasets, a properly trained support vector machine classifier based on this descriptor guarantees an average error below 3%, as opposed to the 8% average error of the best conventional techniques.

Wavelet-Markov local descriptor for detecting fake fingerprints

GRAGNANIELLO, DIEGO;SANSONE, CARLO;
2014-01-01

Abstract

The use of a wavelet-Markov local descriptor, which exploits joint dependencies among wavelet coefficients, for fingerprint liveness detection, is proposed. On the LivDet 2009 datasets, a properly trained support vector machine classifier based on this descriptor guarantees an average error below 3%, as opposed to the 8% average error of the best conventional techniques.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/4776937
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