Multibiometric Fusion Authentication in Wireless Multimedia Environment Using Dynamic Bayesian Method

Zhendong Wu,Jianwu Zhang,Jiajia Yang,Hengli Yue

doi:10.1155/2018/5783976

Zhendong Wu, Jianwu Zhang + Show 2 more

Open Access

https://doi.org/10.1155/2018/5783976

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Abstract

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.

Highlights

Biometric feature analysis has been widely studied for decades as it is a vital way for authentication and safeguard in computer vision
FVC2002 DB1 database was a standard difficult fingerprint dataset with 100 fingers and eight samples for each finger, which was provided by the National Institute of Standards and Technology (NIST)
We proposed a multimodal biometric recognition algorithm and demonstrated its effectiveness

Summary

Introduction

Biometric feature analysis has been widely studied for decades as it is a vital way for authentication and safeguard in computer vision. Traditional biometrics, such as fingerprinting and vein recognition, gradually reveals some of its drawbacks that it can already be assigned and mimicked by forging fingerprints or faces [1]. As fusing features such as facial features, fingerprints, palm prints, sounds, and irises improves the stability, accuracy, and unforgeability of biometrics, multimodal biometric systems could help relieve the problem brought by the single-modal biometric systems and provide tremendous help for more secure authentication and identification. The above improvement in biometric identification demonstrates that there are many advantages of multimodal biometric identification

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