Fingerprint liveness detection consists in extracting measurements, from a fingerprint image, allowing to distinguish between an alive fingerprint image, that is, an image coming from the fingertip of the claimed identity, and an artificial replica. Several algorithms have been proposed so far, but the robustness of their performance has not yet been compared when varying several environmental conditions. In this paper, we present a set of experiments investigating the performance of several feature sets designed for fingerprint liveness detection. In particular we assessed the decrease of performance when varying the pressure and the environmental illumination as well as the size of the region of interest (ROI) used for extracting such features. Experimental results on a large data set show the different dependence of some features sets on the investigated conditions. © 2012 Springer-Verlag Berlin Heidelberg.
Large scale experiments on fingerprint liveness detection / Marcialis, G. L.; Ghiani, L.; Vetter, K.; Morgeneier, D.; Roli, F.. - 7626:(2012), pp. 501-509. (Intervento presentato al convegno Joint IAPR International Workshops on Structural and Syntactic PatternRecognition, SSPR 2012 and Statistical Techniques in Pattern Recognition,SPR 2012 tenutosi a Hiroshima, jpn nel 2012) [10.1007/978-3-642-34166-3_55].
Large scale experiments on fingerprint liveness detection
Ghiani L.;Roli F.
2012-01-01
Abstract
Fingerprint liveness detection consists in extracting measurements, from a fingerprint image, allowing to distinguish between an alive fingerprint image, that is, an image coming from the fingertip of the claimed identity, and an artificial replica. Several algorithms have been proposed so far, but the robustness of their performance has not yet been compared when varying several environmental conditions. In this paper, we present a set of experiments investigating the performance of several feature sets designed for fingerprint liveness detection. In particular we assessed the decrease of performance when varying the pressure and the environmental illumination as well as the size of the region of interest (ROI) used for extracting such features. Experimental results on a large data set show the different dependence of some features sets on the investigated conditions. © 2012 Springer-Verlag Berlin Heidelberg.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
