Multibiometrics Fusion using Acz él-Alsina Triangular Norm

• Ning Wang,
• Li Lu,
• Ge Gao,
• Fanglin Wang,
• Shi Li,

Vol. 8, No. 7, July 28, 2014
10.3837/tiis.2014.07.012, Download Paper (Free):

• Multibiometrics
• Score level fusion
• Iris and face recognition
• Triangular norm

Abstract

Fusing the scores of multibiometrics is a very promising approach to improve the overall systems accuracy and the verification performance. In recent years, there are several approaches towards studying score level fusion of several biometric systems. However, most of them does not consider the genuine and imposter score distributions and result in a higher equal error rate usually. In this paper, a novel score level fusion approach of different biometric systems (dual iris, thermal and visible face traits) based on Acz?-Alsina triangular norm is proposed. It achieves higher identification performance as well as acquires a closer genuine distance and larger imposter distance. The experimental tests are conducted on a virtual multibiometrics database, which merges the challenging CASIA-Iris-Thousand database with noisy samples and the NVIE face database with visible and thermal face images. The rigorous results suggest that significant performance improvement can be achieved after the implementation of multibiometrics. The comparative experiments also ascertain that the proposed fusion approach ouutperforms the state-of-art verification performance.

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