Fisherpalms based palmprint recognition

Xiangqian Wu, Dapeng Zhang, Kuanquan Wang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

357 Citations (Scopus)

Abstract

In this paper, a novel method for palmprint recognition, called Fisherpalms, 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 is used to project palmprints from this high-dimensional original palmprint space to a significantly lower dimensional feature space (Fisherpalm space), in which the palmprints from the different palms can be discriminated much more efficiently. The relationship between the recognition accuracy and the resolution of the palmprint image is also investigated. The experimental results show that, in the proposed method, the palmprint images with resolution 32 × 32 are optimal for medium security biometric systems while those with resolution 64 × 64 are optimal for high security biometric systems. High accuracies (>99%) have been obtained by the proposed method and the speed of this method (responding time ≤ 0.4 s) is rapid enough for real-time palmprint recognition.
Original languageEnglish
Pages (from-to)2829-2838
Number of pages10
JournalPattern Recognition Letters
Volume24
Issue number15
DOIs
Publication statusPublished - 1 Jan 2003

Keywords

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

ASJC Scopus subject areas

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

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