This paper presents a novel two-factor authenticator which hashes tokenized random data and moment based palmprint features to produce a set of private binary string, coined as Discrete-Hashing code. This novel technique requires two factors (random number + authorized biometrics) credentials in order to access the authentication system. Absence of either factor will just handicap the progress of authentication. Besides that, Discrete-Hashing also possesses high discriminatory power, with highly correlated bit strings for intra-class data. Experimental results show that this two-factor authenticator surpasses the classic biometric authenticator in terms of verification rate. Our proposed approach provides a clear separation between genuine and imposter population distributions. This implies that Discrete-Hashing technique allows achievement of zero False Accept Rate (FAR) without jeopardizing the False Reject Rate (FRR) performance, which is hardly possible to conventional biometric systems. © Springer-Verlag Berlin Heidelberg 2004.
CITATION STYLE
Pang, Y. H., Jin, A. T. B., & Ling, D. N. C. (2004). Personal authenticator on the basis of two-factors: Palmprint features and tokenized random data. In Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) (Vol. 3339, pp. 227–236). Springer Verlag. https://doi.org/10.1007/978-3-540-30549-1_21
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