Robust palmprint verification using 2D and 3D features

Dapeng Zhang, Vivek Kanhangad, Nan Luo, Ajay Kumar Pathak

Research output: Journal article publicationJournal articleAcademic researchpeer-review

82 Citations (Scopus)

Abstract

This paper presents a new personal authentication system that simultaneously exploits 2D and 3D palmprint features. The objective of our work is to improve accuracy and robustness of existing palmprint authentication systems using 3D palmprint features. The proposed multilevel framework for personal authentication efficiently utilizes the robustness (against spoof attacks) of the 3D features and the high discriminating power of the 2D features. The developed system uses an active stereo technique, structured light, to simultaneously capture 3D image or range data and a registered intensity image of the palm. The surface curvature feature based method is investigated for 3D palmprint feature extraction while Gabor feature based competitive coding scheme is used for 2D representation. We comparatively analyze these representations for their individual performance and attempt to achieve performance improvement using the proposed multilevel matcher that utilizes fixed score level combination scheme to integrate information. Our experiments on a database of 108 subjects achieved significant improvement in performance with the integration of 3D features as compared to the case when 2D palmprint features alone are employed. We also present experimental results to demonstrate that the proposed biometric system is extremely difficult to circumvent, as compared to the currently proposed palmprint authentication approaches in the literature.
Original languageEnglish
Pages (from-to)358-368
Number of pages11
JournalPattern Recognition
Volume43
Issue number1
DOIs
Publication statusPublished - 1 Jan 2010

Keywords

  • 3D palmprint features
  • Biometrics
  • Gabor features
  • Multilevel matching
  • Palmprint verification

ASJC Scopus subject areas

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

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