Multibiometric Fusion Authentication in Wireless Multimedia Environment Using Dynamic Bayesian Method

Single biometric method has been widely used in the field of wireless multimedia authentication. However, it is vulnerable to spoofing and limited accuracy. To tackle this challenge, in this paper, we propose a multimodal fusion method for fingerprint and voiceprint by using a dynamic Bayesian method, which takes full advantage of the feature specificity extracted by a single biometrics project and authenticates users at the decision-making level. We demonstrate that this method can be extended to more modal biometric authentication and can achieve flexible accuracy of the authentication. The experiment of the method shows that the recognition rate and stability have been greatly improved, which achieves 4.46% and 5.94%, respectively, compared to the unimodal. Furthermore, it also increases 1.94% when compared with general multimodal methods for the biometric fusion recognition.