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Sorted Index Numbers for Privacy Preserving Face Recognition

Abstract

This paper presents a novel approach for changeable and privacy preserving face recognition. We first introduce a new method of biometric matching using the sorted index numbers (SINs) of feature vectors. Since it is impossible to recover any of the exact values of the original features, the transformation from original features to the SIN vectors is noninvertible. To address the irrevocable nature of biometric signals whilst obtaining stronger privacy protection, a random projection-based method is employed in conjunction with the SIN approach to generate changeable and privacy preserving biometric templates. The effectiveness of the proposed method is demonstrated on a large generic data set, which contains images from several well-known face databases. Extensive experimentation shows that the proposed solution may improve the recognition accuracy.

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Correspondence to Yongjin Wang.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Wang, Y., Hatzinakos, D. Sorted Index Numbers for Privacy Preserving Face Recognition. EURASIP J. Adv. Signal Process. 2009, 260148 (2009). https://doi.org/10.1155/2009/260148

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Keywords

  • Feature Vector
  • Quantum Information
  • Recognition Accuracy
  • Full Article
  • Privacy Protection
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