An uncorrelated fisherface approach for face and palmprint recognition

Xiao Yuan Jing, Chen Lu, Dapeng Zhang

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

5 Citations (Scopus)

Abstract

The Fisherface method is a most representative method of the linear discrimination analysis (LDA) technique. However, there persist in the Fisherface method at least two areas of weakness. The first weakness is that it cannot make the achieved discrimination vectors completely satisfy the statistical uncorrelation while costing a minimum of computing time. The second weakness is that not all the discrimination vectors are useful in pattern classification. In this paper, we propose an uncorrelated Fisherface approach (UFA) to improve the Fisherface method in these two areas. Experimental results on different image databases demonstrate that UFA outperforms the Fisherface method and the uncorrelated optimal discrimination vectors (UODV) method.
Original languageEnglish
Title of host publicationAdvances in Biometrics - International Conference, ICB 2006, Proceedings
Pages682-687
Number of pages6
Publication statusPublished - 15 Jun 2006
EventInternational Conference on Biometrics, ICB 2006 - Hong Kong, Hong Kong
Duration: 5 Jan 20067 Jan 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3832 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceInternational Conference on Biometrics, ICB 2006
CountryHong Kong
CityHong Kong
Period5/01/067/01/06

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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