Class-distribution preserving transform for face biometric data security

Y. C. Feng*, Pong Chi YUEN

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

10 Citations (Scopus)

Abstract

This paper addresses the face data variations problem in biometric cryptosystems in which the cryptographic technique is applied to biometric system. To overcome the limitation, this paper introduce a new class-distribution preserving transform to biometric cryptosystems. The basic idea is to transform a real value face feature vector to a binary feature vector using a random points set. The proposed transform is integrated into a BCH coding technique. Fisherface algorithm is used for feature extraction and ORL face database is selected for experiments. It is shown that only around 0.8% accuracy is degraded in comparing with the original Fisherface algorithm while the system security can be enhanced by 126 bits.

Original languageEnglish
Title of host publication2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07
PagesII141-II144
DOIs
Publication statusPublished - 2007
Event2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07 - Honolulu, HI, United States
Duration: 15 Apr 200720 Apr 2007

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2
ISSN (Print)1520-6149

Conference

Conference2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07
Country/TerritoryUnited States
CityHonolulu, HI
Period15/04/0720/04/07

Scopus Subject Areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

User-Defined Keywords

  • Biometric cryptosystems
  • Biometric data security

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