Score level fusion of multimodal biometrics using triangular norms

Authors:
Madasu Hanmandlu;Jyotsana Grover;Ankit Gureja;H. M. Gupta
Affiliations:
Indian Institute of Technology, Delhi, India;Indian Institute of Technology, Delhi, India;Jamia Millia Islamia, Delhi, India;Indian Institute of Technology, Delhi, India
Venue:
Pattern Recognition Letters
Year:
2011

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Abstract

A multimodal biometric system that alleviates the limitations of the unimodal biometric systems by fusing the information from the respective biometric sources is developed. A general approach is proposed for the fusion at score level by combining the scores from multiple biometrics using triangular norms (t-norms) due to Hamacher, Yager, Frank, Schweizer and Sklar, and Einstein product. This study aims at tapping the potential of t-norms for multimodal biometrics. The proposed approach renders very good performance as it is quite computationally fast and outperforms the score level fusion using the combination approach (min, mean, and sum) and classification approaches like SVM, logistic linear regression, MLP, etc. The experimental evaluation on three databases confirms the effectiveness of score level fusion using t-norms.