Menrit S. Fahmy

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Support Vector Machines or SVM is one of the most successful and powerful statistical learning classification techniques. It has been also implemented in the biometric field. In this paper we propose the use of SVM as a fusion tool. We propose a system that fuses the classification obtained from the iris biometric and the fingerprint biometric. In addition,(More)
This paper presents the score level fusion of multimodal biometrics using Hanman-Anirban entropy function. Entropy function captures the uncertainty in the scores. The experimental results ascertain that Entropy based score level fusion outperforms over existing methods of score level fusion such as t-norms, sum and max. We have validated our claim on(More)
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