生物识别与生物统计学杂志

Multimodal Biometrics for Robust Fusion Systems using Logic Gat es

Abstract

N. Celik, N. Manivannan, W. Balachandran and S. Kosunalp

Many professionals indicate that unimodal biometric recognition systems have many shortcomings associated with performance accuracy rates. In order to make the system design more robust, we propose a multimodal biometric which includes fingerprint and face recognition using logical AND operators at decision-level fusion. In this paper, we also discuss some concerns about the security issues regarding the identification and verification processes for the multimodal recognition system against invaders and threatening attackers. While the unimodal fingerprint and face biometric gives recognition rate of 94% and 90.8% respectively, the multi-modal approach was giving a recognition rate of 98% at the decision level fusion, showing an improvement in the accuracy. Also, both the FAR and FRR have been considerably reduced, showing that the multi-modal system implemented is more robust.