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Fuzzy 2DLDA for face recognition

  • Southeast University, Nanjing
  • Hong Kong Polytechnic University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

This paper proposes a new method of face image feature extraction, namely, the fuzzy 2DLDA (F2DLDA) based on the 2D fisher discriminant criterion and fuzzy set theory. In the proposed method, we calculate membership degree matrix by FKNN, then we incorporate the membership degree into the definition of the between-class scatter matrix and within-class scatter matrix and get the fuzzy between-class scatter matrix and fuzzy within-class scatter matrix. Experiments on the ORL and FERET face databases show that the new method can work well.

Original languageEnglish
Title of host publicationProceedings of the 2009 Chinese Conference on Pattern Recognition, CCPR 2009, and the 1st CJK Joint Workshop on Pattern Recognition, CJKPR
Pages470-473
Number of pages4
DOIs
StatePublished - 2009
Externally publishedYes
Event2009 Chinese Conference on Pattern Recognition, CCPR 2009 and the 1st CJK Joint Workshop on Pattern Recognition, CJKPR - Nanjing, China
Duration: 4 Nov 20096 Nov 2009

Publication series

NameProceedings of the 2009 Chinese Conference on Pattern Recognition, CCPR 2009, and the 1st CJK Joint Workshop on Pattern Recognition, CJKPR

Conference

Conference2009 Chinese Conference on Pattern Recognition, CCPR 2009 and the 1st CJK Joint Workshop on Pattern Recognition, CJKPR
Country/TerritoryChina
CityNanjing
Period4/11/096/11/09

Keywords

  • 2DLDA
  • Face recognition
  • Feature extraction
  • Fuzzy
  • LDA

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