Personal identification using periocular skin texture

  • Authors:
  • Philip E. Miller;Allen W. Rawls;Shrinivas J. Pundlik;Damon L. Woodard

  • Affiliations:
  • Clemson University, Clemson, SC;Clemson University, Clemson, SC;Clemson University, Clemson, SC;Clemson University, Clemson, SC

  • Venue:
  • Proceedings of the 2010 ACM Symposium on Applied Computing
  • Year:
  • 2010

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Abstract

In this paper, we propose the use of periocular skin texture as a biometric modality. Salient skin texture features are extracted and represented using Local Binary Patterns (LBPs). Matching is performed using CityBlock distance as a measure of similarity. We investigate the use of each periocular region separately in addition to their use in conjunction. Verification and identification experiments involving over 400 subjects were performed using a datasets constructed from the FRGC and FERET datasets. Reported recognition rates of nearly 90%, demonstrate the effectiveness of this novel technique.