Skip to content

Advertisement

  • Research Article
  • Open Access

Sorted Index Numbers for Privacy Preserving Face Recognition

EURASIP Journal on Advances in Signal Processing20092009:260148

https://doi.org/10.1155/2009/260148

  • Received: 30 September 2008
  • Accepted: 18 August 2009
  • Published:

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.

Keywords

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

Publisher note

To access the full article, please see PDF.

Authors’ Affiliations

(1)
The Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto, 10 King's College Road, Toronto, ON, Canada, M5S 3G4

Copyright

Advertisement