Palmprint recognition using Fisher's linear discriminant

Xiang Qian Wu, Kuan Quan Wang, Dapeng Zhang

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

16 Citations (Scopus)

Abstract

In this paper, a novel method for palmprint recognition is proposed. In this method, each pixel of a palmprint image is considered as a coordinate in a high-dimensional image space. A linear projection based on Fisher's linear discriminant (FLD) is used to project palmprints from this high-dimensional space to a significantly lower dimensional feature space, in which the ratio of the determinant of the between-class scatter to that of the within-class scatter is maximized. High accuracies of 99% and 99.2% have been obtained in one-to-one matching and one-to-300 matching test respectively and the speed of this method is rapid enough for real-time palmprint recognition.
Original languageEnglish
Title of host publicationInternational Conference on Machine Learning and Cybernetics
Pages3150-3154
Number of pages5
Volume5
Publication statusPublished - 1 Dec 2003
Event2003 International Conference on Machine Learning and Cybernetics - Xi'an, China
Duration: 2 Nov 20035 Nov 2003

Conference

Conference2003 International Conference on Machine Learning and Cybernetics
CountryChina
CityXi'an
Period2/11/035/11/03

Keywords

  • Biometrics
  • Fisher's linear discriminant
  • Linear projection
  • Palmprint recognition

ASJC Scopus subject areas

  • Artificial Intelligence

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