Biometric scores fusion based on total error rate minimization

Authors:
Kar-Ann Toh;Jaihie Kim;Sangyoun Lee
Affiliations:
Biometrics Engineering Research Center, School of Electrical & Electronic Engineering, Yonsei University, 134 Shinchon-dong, Seodaemun-gu, Seoul, 120-749, Korea;Biometrics Engineering Research Center, School of Electrical & Electronic Engineering, Yonsei University, 134 Shinchon-dong, Seodaemun-gu, Seoul, 120-749, Korea;Biometrics Engineering Research Center, School of Electrical & Electronic Engineering, Yonsei University, 134 Shinchon-dong, Seodaemun-gu, Seoul, 120-749, Korea
Venue:
Pattern Recognition
Year:
2008

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Abstract

This paper addresses the biometric scores fusion problem from the error rate minimization point of view. Comparing to the conventional approach which treats fusion classifier design and performance evaluation as a two-stage process, this work directly optimizes the target performance with respect to fusion classifier design. Based on a smooth approximation to the total error rate of identity verification, a deterministic solution is proposed to solve the fusion optimization problem. The proposed method is applied to a face and iris verification fusion problem addressing the demand for high security in the modern networked society. Our empirical evaluations show promising potential in terms of decision accuracy and computing efficiency.