Eigenspace-based face hashing

David C.L. Ngo, Andrew B.J. Teoh, Alwyn Goh

Research output: Chapter in Book/Report/Conference proceedingChapter

13 Citations (Scopus)

Abstract

We present a novel approach to generating cryptographic keys from biometrics. In our approach, the PCA coefficients of a face image are discretised using a bit-extraction method to n bits. We compare performance results obtained with and without the discretisation procedure applied to several PCA-based methods (including PCA, PCA with weighing coefficients, PCA on Wavelet Subband, and LDA) on a combined face image database. Results show that the discretisation step consistently increases the performance.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsDavid Zhang, Anil K. Jain
PublisherSpringer Verlag
Pages195-199
Number of pages5
ISBN (Print)3540221468, 9783540221463
DOIs
Publication statusPublished - 2004

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3072
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Ngo, D. C. L., Teoh, A. B. J., & Goh, A. (2004). Eigenspace-based face hashing. In D. Zhang, & A. K. Jain (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 195-199). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3072). Springer Verlag. https://doi.org/10.1007/978-3-540-25948-0_27