3-D palmprint recognition with joint line and orientation features

Wei Li, Dapeng Zhang, Lei Zhang, Guangming Lu, Jingqi Yan

Research output: Journal article publicationJournal articleAcademic researchpeer-review

55 Citations (Scopus)

Abstract

2-D palmprint has been recognized as an effective biometric identifier in the past decade. Recently, 3-D palmprint recognition was proposed to further improve the performance of palmprint systems. This paper presents a simple yet efficient scheme for 3-D palmprint recognition. After calculating and enhancing the mean-curvature image of the 3-D palmprint data, we extract both line and orientation features from it. The two types of features are then fused at either score level or feature level for the final 3-D palmprint recognition. The experiments on The Hong Kong Polytechnic University 3-D palmprint database, which contains 8000 samples from 400 palms show that the proposed feature extraction and fusion methods lead to promising performance.
Original languageEnglish
Article number5551238
Pages (from-to)274-279
Number of pages6
JournalIEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews
Volume41
Issue number2
DOIs
Publication statusPublished - 1 Mar 2011

Keywords

  • 3-D palmprint identification
  • biometrics
  • feature fusion
  • mean curvature

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Information Systems
  • Human-Computer Interaction
  • Computer Science Applications
  • Electrical and Electronic Engineering

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