Multimodal biometric authentication based on score level fusion of finger biometrics

In this article, we propose a novel finger multimodal biometric authentication that combines finger vein, fingerprint, finger shape and finger knuckle print features of a single human finger. The proposed multimodal biometrics provides score-level fusion approach based on triangular norm with four finger biometric traits, instead of two or three ones combined in the previous approaches. The experimental evaluations and analysis are conducted on a merged multimodal biometrics database. The results show that the proposed score-level fusion approach using triangular norm obtains a larger distance between genuine and imposter score distribution as well as achieves lower error rates. Moreover, the comparison results suggest that the proposed score level fusion of finger biometrics using triangular norm outperforms the state-of-the-art approaches.