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Title: | Score level fusion of multimodal biometrics using triangular norms |
Authors: | Grover, Jyotsana |
Keywords: | Computer Science Biometrics Triangular norms Multimodal authentication Score level fusion Decidability index |
Issue Date: | Oct-2011 |
Publisher: | Elsevier |
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. |
URI: | https://www.sciencedirect.com/science/article/pii/S0167865511002133#aep-keywords-id15 http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/8669 |
Appears in Collections: | Department of Computer Science and Information Systems |
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