Unified framework for automated iris segmentation using distantly acquired face images

Chun Wei Tan, Ajay Kumar Pathak

Research output: Journal article publicationJournal articleAcademic researchpeer-review

92 Citations (Scopus)

Abstract

Remote human identification using iris biometrics has high civilian and surveillance applications and its success requires the development of robust segmentation algorithm to automatically extract the iris region. This paper presents a new iris segmentation framework which can robustly segment the iris images acquired using near infrared or visible illumination. The proposed approach exploits multiple higher order local pixel dependencies to robustly classify the eye region pixels into iris or noniris regions. Face and eye detection modules have been incorporated in the unified framework to automatically provide the localized eye region from facial image for iris segmentation. We develop robust postprocessing operations algorithm to effectively mitigate the noisy pixels caused by the misclassification. Experimental results presented in this paper suggest significant improvement in the average segmentation errors over the previously proposed approaches, i.e., 47.5%, 34.1%, and 32.6% on UBIRIS.v2, FRGC, and CASIA.v4 at-a-distance databases, respectively. The usefulness of the proposed approach is also ascertained from recognition experiments on three different publicly available databases.
Original languageEnglish
Article number6199979
Pages (from-to)4068-4079
Number of pages12
JournalIEEE Transactions on Image Processing
Volume21
Issue number9
DOIs
Publication statusPublished - 31 Aug 2012

Keywords

  • Biometrics
  • iris recognition
  • iris segmentation
  • unconstrained iris recognition

ASJC Scopus subject areas

  • Software
  • Medicine(all)
  • Computer Graphics and Computer-Aided Design

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