Cancellable biometrics and multispace random projections

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

In this paper, a generic cancellable biometrics formulation is proposed by first transforming the raw biometrics data into a fixed length feature vector, then subsequently re-projecting the feature vector onto a sequence of random subspaces specified by the tokenised random vectors. Since random subspace is user-specific, the formulation can be extended to multiple random subspaces for different individuals to amplify the interclass variation whilst maintain the intra-class variation in biometrics verification setting. The privacy invasion and non-revocable problems in biometrics could be resolved by revocation of resulting feature through the random subspace replacement. This formulation furthermore enhances recognition effectiveness as arising from the Multispace Random Projections of biometric and external random inputs.

Original languageEnglish
Title of host publication2006 Conference on Computer Vision and Pattern Recognition Workshop
DOIs
Publication statusPublished - 2006
Event2006 Conference on Computer Vision and Pattern Recognition Workshops - New York, NY, United States
Duration: 2006 Jun 172006 Jun 22

Publication series

NameProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Volume2006
ISSN (Print)1063-6919

Other

Other2006 Conference on Computer Vision and Pattern Recognition Workshops
CountryUnited States
CityNew York, NY
Period06/6/1706/6/22

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition

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