Novel multimodal template generation algorithm

Abstract

Multimodal biometric system has emerged as a highly successful new approach to combat problems of unimodal biometric system such as intraclass variability, interclass similarity, data quality, non-universality, and sensitivity to noise. The idea behind the cancelable biometric or cancelability is to transform a biometric data or feature into a new one so that the stored biometric template can be easily changed in a biometric security system. In this paper, we present a novel architecture for template generation within the context of the cancelable multimodal system. We develop a novel cancelable biometric template generation algorithm using random projection and transformation-based feature extraction and selection. We further validate the performance of the proposed algorithm on a virtual multimodal face and ear database.