Fusion for multimodal biometric identification

Authors:
Yongjin Lee;Kyunghee Lee;Hyungkeun Jee;Younhee Gil;Wooyong Choi;Dosung Ahn;Sungbum Pan
Affiliations:
Biometrics Technology Research Team, Electronics and Telecommunications Research Institute, Daejeon, Korea;Department of Electrical Engineering, The University of Suwon, Korea;Biometrics Technology Research Team, Electronics and Telecommunications Research Institute, Daejeon, Korea;Biometrics Technology Research Team, Electronics and Telecommunications Research Institute, Daejeon, Korea;Biometrics Technology Research Team, Electronics and Telecommunications Research Institute, Daejeon, Korea;Biometrics Technology Research Team, Electronics and Telecommunications Research Institute, Daejeon, Korea;Division of Information and Control Measurement Engineering, Chosun University, Korea
Venue:
AVBPA'05 Proceedings of the 5th international conference on Audio- and Video-Based Biometric Person Authentication
Year:
2005

Citing 4
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Abstract

In this paper, we investigate fusion methods for multimodal identification using several unimodal identification results. One fingerprint identification system and two face identification systems are used as fusion sources. We discuss rank level and score level fusion methods. Whereas the latter combines similarity scores, the other one combines the orders of the magnitudes of the similarity scores. For rank level methods, Borda Count and Bayes Fuse are considered and, for score level methods, Sum Rule and Binary Classification Approach are considered. Especially, we take a more detailed look at Binary Classification Approach, which simplifies a multiple class problem into a binary class problem. Finally, we compare experimental results using the fusion methods in different combinations of the sources.