Improvements on the linear discrimination technique with application to face recognition

Xiao Yuan Jing, Dapeng Zhang, Yong Fang Yao

Research output: Journal article publicationJournal articleAcademic researchpeer-review

20 Citations (Scopus)

Abstract

In this paper, new improvements for the linear discrimination technique are proposed. These improvements include effective solutions for the small sample size problem, the selection of appropriate principal component and more accurate within-class scatter estimation for the Fisher criterion. The effectiveness of our approach is proved by experimental results on the Yale face database.
Original languageEnglish
Pages (from-to)2695-2701
Number of pages7
JournalPattern Recognition Letters
Volume24
Issue number15
DOIs
Publication statusPublished - 1 Jan 2003

Keywords

  • Face recognition
  • Linear discrimination
  • Principal component selection
  • Small sample size problem
  • Within-class scatter estimation

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

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