Hand biometric recognition based on fused hand geometry and vascular patterns

Gitae Park, Soowon Kim

Research output: Contribution to journalArticlepeer-review

28 Citations (Scopus)

Abstract

A hand biometric authentication method based on measurements of the user's hand geometry and vascular pattern is proposed. To acquire the hand geometry, the thickness of the side view of the hand, the K-curvature with a hand-shaped chain code, the lengths and angles of the finger valleys, and the lengths and profiles of the fingers were used, and for the vascular pattern, the direction-based vascular-pattern extraction method was used, and thus, a new multimodal biometric approach is proposed. The proposed multimodal biometric system uses only one image to extract the feature points. This system can be configured for low-cost devices. Our multimodal biometric-approach hand-geometry (the side view of the hand and the back of hand) and vascular-pattern recognition method performs at the score level. The results of our study showed that the equal error rate of the proposed system was 0.06%.

Original languageEnglish
Pages (from-to)2895-2910
Number of pages16
JournalSensors (Switzerland)
Volume13
Issue number3
DOIs
Publication statusPublished - 2013 Mar

Keywords

  • Hand biometric
  • Hand geometry
  • Multimodal biometric
  • Vascular-pattern recognition

ASJC Scopus subject areas

  • Analytical Chemistry
  • Information Systems
  • Atomic and Molecular Physics, and Optics
  • Biochemistry
  • Instrumentation
  • Electrical and Electronic Engineering

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