Multimodal biometric person authentication using fingerprint, face features

Authors:
Tran Binh Long;Le Hoang Thai;Tran Hanh
Affiliations:
Department of Computer Science, University of Lac Hong, DongNai, Vietnam;Department of Computer Science, Ho Chi Minh City University of Science, HoChiMinh, Vietnam;Department of Computer Science, University of Lac Hong, DongNai, Vietnam
Venue:
PRICAI'12 Proceedings of the 12th Pacific Rim international conference on Trends in Artificial Intelligence
Year:
2012

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Abstract

In this paper, the authors present a multimodal biometric system using face and fingerprint features with the incorporation of Zernike Moment (ZM) and Radial Basis Function (RBF) Neural Network for personal authentication. It has been proven that face authentication is fast but not reliable while fingerprint authentication is reliable but inefficient in database retrieval. With regard to this fact, our proposed system has been developed in such a way that it can overcome the limitations of those uni-modal biometric systems and can tolerate local variations in the face or fingerprint image of an individual. The experimental results demonstrate that our proposed method can assure a higher level of forge resistance in comparison to that of the systems with single biometric traits.