Human identification using KnuckleCodes

Ajay Kumar Pathak, Yingbo Zhou

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

75 Citations (Scopus)


The usage of finger knuckle images for personal identification has shown promising results and generated lot of interest in biometrics. In this work, we investigate a new approach for efficient and effective personal identification using KnuckleCodes. The enhanced knuckle images are employed to generate KnuckleCodes using localized Radon transform that can efficiently characterize random curved lines and creases. The similarity between two KnuckleCodes is computed from the minimum matching distance that can account for the variations resulting from translation and positioning of fingers. The feasibility of the proposed approach is investigated on the finger knuckle database from 158 subjects. The experimental results, i.e., equal error rate of 1.08% and rank one recognition rate of 98.6%, suggest the utility of the proposed approach for online human identification.
Original languageEnglish
Title of host publicationIEEE 3rd International Conference on Biometrics
Subtitle of host publicationTheory, Applications and Systems, BTAS 2009
Publication statusPublished - 16 Dec 2009
EventIEEE 3rd International Conference on Biometrics: Theory, Applications and Systems, BTAS 2009 - Washington, DC, United States
Duration: 28 Sep 200930 Sep 2009


ConferenceIEEE 3rd International Conference on Biometrics: Theory, Applications and Systems, BTAS 2009
Country/TerritoryUnited States
CityWashington, DC

ASJC Scopus subject areas

  • Biotechnology
  • Computational Theory and Mathematics
  • Computer Vision and Pattern Recognition

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