A novel Fisher criterion based St-subspace linear discriminant method for face recognition

Wensheng Chen*, Pong Chi YUEN, Jian Huang, Jianhuang Lai

*Corresponding author for this work

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

2 Citations (Scopus)


In this paper, a novel Fisher criterion is introduced and shown to be equivalent to the traditional Fisher criterion. Based on this new Fisher criterion and simultaneous diagonalization technique, a St-subspace Fisher discriminant (St-SFD) method is developed to deal with the small sample size (S3) problem in face recognition. The proposed method overcomes some drawbacks of existing LDA based algorithms. Also, our method has good computational complexity. Two public available databases, namely ORL and FERET databases, are exploited to evaluate the proposed algorithm. Comparing with existing LDA-based methods in solving the S3 problem, the proposed S t-SFD method gives the best performance.

Original languageEnglish
Title of host publicationComputational Intelligence and Security - International Conference, CIS 2005, Proceedings
PublisherSpringer Verlag
Number of pages8
ISBN (Print)3540308180, 9783540308188
Publication statusPublished - 2005
EventInternational Conference on Computational Intelligence and Security, CIS 2005 - Xi'an, China
Duration: 15 Dec 200519 Dec 2005

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3801 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


ConferenceInternational Conference on Computational Intelligence and Security, CIS 2005

Scopus Subject Areas

  • Theoretical Computer Science
  • Computer Science(all)


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