Abstract
Recently, cancelable biometrics emerged as one of the highly effective methods of template protection. The concept behind the cancelable biometrics or cancelability is a transformation of a biometric data or extracted feature into an alternative form, which cannot be used by the imposter or intruder easily, and can be revoked if compromised. In this paper, we present a novel architecture for template generation in the context of situation awareness system in real and virtual applications. We develop a novel cancelable biometric template generation algorithm utilizing random biometric fusion, random projection and selection. Proposed random cross-folding method generate cancelable biometric template from multiple biometric traits. We further validate the performance of the proposed algorithm using a virtual multimodal face and ear database.
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