The protection of the templates stored in a biometric recognition system represents an issue of paramount importance for the security and privacy of the enrolled users, and directly affects the successful deployment of the system itself. In this paper we propose a protected on-line signature recognition system where the properties of Universal Background Models are exploited to provide a small dimensionality and a limited intra-class variability signature representation. The reported experimental results show that the employed signature representation and protection scheme allow to reach high recognition accuracy while providing protection to the considered biometric data.
Maiorana, E., Argones Rua, E., Alba, J.C., Campisi, P. (2011). Eigen-model Projections for Protected On-line Signature Recognition. In Proceedings of the COST 2101 European Workshop, BioID 2011,.
Eigen-model Projections for Protected On-line Signature Recognition
MAIORANA, EMANUELE;CAMPISI, PATRIZIO
2011-01-01
Abstract
The protection of the templates stored in a biometric recognition system represents an issue of paramount importance for the security and privacy of the enrolled users, and directly affects the successful deployment of the system itself. In this paper we propose a protected on-line signature recognition system where the properties of Universal Background Models are exploited to provide a small dimensionality and a limited intra-class variability signature representation. The reported experimental results show that the employed signature representation and protection scheme allow to reach high recognition accuracy while providing protection to the considered biometric data.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
