Poulose Jacob,K; Binsu, Kovoor C; Supriya, M H(International Journal of Computer Science and Communication, June , 2011)
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Abstract:
Any automatically measurable, robust and distinctive physical characteristic or personal trait that can be used to
identify an individual or verify the claimed identity of an individual, referred to as biometrics, has gained significant
interest in the wake of heightened concerns about security and rapid advancements in networking, communication
and mobility. Multimodal biometrics is expected to be ultra-secure and reliable, due to the presence of multiple and
independent—verification clues. In this study, a multimodal biometric system utilising audio and facial signatures
has been implemented and error analysis has been carried out. A total of one thousand face images and 250 sound
tracks of 50 users are used for training the proposed system. To account for the attempts of the unregistered signatures
data of 25 new users are tested. The short term spectral features were extracted from the sound data and Vector
Quantization was done using K-means algorithm. Face images are identified based on Eigen face approach using
Principal Component Analysis. The success rate of multimodal system using speech and face is higher when compared
to individual unimodal recognition systems
Description:
International Journal of Computer Science and Communication Vol. 2, No. 1, January-June 2011, pp. 143-147