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A Novel Cross Folding Algorithm for Multimodal Cancelable Biometrics

A Novel Cross Folding Algorithm for Multimodal Cancelable Biometrics

Padma P. Paul, Marina L. Gavrilova
Copyright: © 2012 |Volume: 4 |Issue: 3 |Pages: 18
ISSN: 1942-9045|EISSN: 1942-9037|EISBN13: 9781466614215|DOI: 10.4018/jssci.2012070102
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MLA

Paul, Padma P., and Marina L. Gavrilova. "A Novel Cross Folding Algorithm for Multimodal Cancelable Biometrics." IJSSCI vol.4, no.3 2012: pp.20-37. http://doi.org/10.4018/jssci.2012070102

APA

Paul, P. P. & Gavrilova, M. L. (2012). A Novel Cross Folding Algorithm for Multimodal Cancelable Biometrics. International Journal of Software Science and Computational Intelligence (IJSSCI), 4(3), 20-37. http://doi.org/10.4018/jssci.2012070102

Chicago

Paul, Padma P., and Marina L. Gavrilova. "A Novel Cross Folding Algorithm for Multimodal Cancelable Biometrics," International Journal of Software Science and Computational Intelligence (IJSSCI) 4, no.3: 20-37. http://doi.org/10.4018/jssci.2012070102

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Abstract

Multimodal biometric systems have emerged as 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. However, one major issue pertinent to unimodal system remains, which has to do with actual biometric characteristics of users being permanent and their number being limited. Thus, if a user’s biometric is compromised, it might be impossible or highly difficult to replace it in a particular system. The concept of 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, the authors present a novel solution for cancelable biometrics in a multimodal system. They develop a new cancelable biometric template generation algorithm using random projection and transformation-based feature extraction and selection. Performance of the proposed algorithm is validated on a virtual multi-modal face and ear database.

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