Performance evaluation of score level fusion in multimodal biometric systems
Pattern Recognition
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Proceedings of the International Conference & Workshop on Emerging Trends in Technology
Applied Computational Intelligence and Soft Computing
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Using multimodal biometric systems that consolidate evidence from multiple biometric sources can remove such as noisy sensor data, no-universality problems. In this paper, fingerprint, palm-print and hand-geometry are combined for person identity verification. Unlike other multimodal biometric systems, three biometrics can be taken from the same image. Wavelet transform to extract the features from fingerprint and palm-print is used and hand-geometry feature (such as width and length) is extracted after the pre-processing phase. We employ feature fusion and mach score fusion together to establish identity. The system was tested on a database of 98 persons. The test performance results indicate the possibility of the combination.