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.File in questo prodotto:
Non ci sono file associati a questo prodotto.
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.