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Journal of Information Science and Engineering, Vol. 21 No. 6, pp. 1121-1137 (November 2005)

A Face and Speech Biometric Verification System Using a Simple Bayesian Structure

Andrew B. J. Teoh, S. A. Samad* and A. Hussain*
Faculty of Information Science and Technology (FIST)
Multimedia University
75450, Melaka, Malaysia
*Electrical, Electronic and System Engineering Department
National University of Malaysia
43600, Bangi, Malaysia
E-mail: {salina; aini}

Identity verification systems that use a mono modal biometric always have to contend with sensor noise and limitations of the feature extractor and matcher, while combining information from different biometrics modalities may well provide higher and more consistent performance levels. However, an intelligent scheme is required to fuse the decisions produced by the individual sensors. This paper presents a decision fusion technique for a bimodal biometric verification system that makes use of facial and speech biometrics. The decision fusion schemes considered have simple Bayesian structures (SBS) that particularize the univariat Gaussian density function, Beta density function or Parzen window density estimation. SBS has advantages in terms of computation speed, storage space and its open framework. The performances of SBS is evaluated and compared with that of other classical classification approaches, such as sum rule and Multilayer Perceptron, on a bimodal database.

Keywords: bimodal biometrics, face module, speech module, simple bayesian structure, decision fusion

Full Text () Retrieve PDF document (200511_02.pdf)

Received April 28, 2003; revised August 11, 2003; accepted July 8, 2004.
Communicated by Kuo-Chin Fan.