Conventional multimodal biometric identification systems tend to have larger memory footprint, slower processing speeds and a higher implementation and operational cost. In this paper we propose a state of the art framework for multimodal biometric identification system which can be adapted for any type of biometrics to provide smaller memory footprint and faster implementation than the conventional multimodal biometrics systems. The proposed framework is verified by development of a fingerprint and iris based fusion system which utilizes a single Hamming Distance matcher. Extensive testing is performed on the system running in identification mode and the results show that the system not only provides higher accuracy than the individual unimodal system but also the results are comparable to the conventional system.
|International Journal of Bio-Science and Bio-Technology
|Published - Dec 2009