Personal identification using periocular skin texture

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.