Face Verification Based on DCT Templates with Pseudo-Random Permutations

Authors:
Marco Grassi;Marcos Faundez-Zanuy
Affiliations:
Department of Biomedical, Electronic and Telecommunication Engineering, Università Politecnica delle Marche, Ancona, Italy;Escola Universitària Politècnica de Mataró (Adscrita a la UPC), Mataró, Spain
Venue:
Proceedings of the 2009 conference on Neural Nets WIRN09: Proceedings of the 19th Italian Workshop on Neural Nets, Vietri sul Mare, Salerno, Italy, May 28--30 2009
Year:
2009

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Abstract

Biometric template security and privacy are a great concern of biometric systems, because unlike passwords and tokens, compromised biometric templates cannot be revoked and reissued. In this paper we present a protection scheme for a face verification system based on a user dependent pseudo-random ordering of the DCT template coefficients and MPL and RBF Neural Networks for classification. In addition to privacy enhancement, because a hacker can hardly match a fake biometric sample without knowing the pseudo-random ordering this scheme, the proposed system also increases the biometric recognition performance.