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Proceedings Paper

Authentication-invariant cancellable biometric filters for illumination-tolerant face verification
Author(s): Marios Savvides; B. V. K. Vijaya Kumar; Pradeep K. Khosla
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Paper Abstract

In this paper we address the issue of producing cancelable biometric templates; a necessary feature in the deployment of any biometric authentication system. We propose a novel scheme that encrypts the training images used to synthesize the single (minimum average correlation energy) filter for biometric authentication. We show theoretically that convolving the training images with any random convolution kernel prior to building the filter does not change the resulting correlation output peak-to-sidelobe ratios, thus preserving the authentication performance. However, different templates can be obtained from the same biometric by varying the convolution kernels thus enabling the cancelability of the templates. We evaluate the proposed method using the illumination subset of the CMU pose, illumination, expressions (PIE) face dataset and show that we are still able to achieve 100% face verification using the proposed encryption scheme. Our proposed method is interesting from a pattern recognition theory point of view, as we are able to 'encrypt' the data and perform recognition in the encrypted domain that performs as well as the unencrypted case, for a variety of encryption kernels; we show analytically that the recognition performance remains invariant to the proposed encryption scheme, while retaining the desired shift-invariance property of correlation filters.

Paper Details

Date Published: 25 August 2004
PDF: 8 pages
Proc. SPIE 5404, Biometric Technology for Human Identification, (25 August 2004); doi: 10.1117/12.542997
Show Author Affiliations
Marios Savvides, Carnegie Mellon Univ. (United States)
B. V. K. Vijaya Kumar, Carnegie Mellon Univ. (United States)
Pradeep K. Khosla, Carnegie Mellon Univ. (United States)

Published in SPIE Proceedings Vol. 5404:
Biometric Technology for Human Identification
Anil K. Jain; Nalini K. Ratha, Editor(s)

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