Towards online iris and periocular recognition under relaxed imaging constraints

Chun Wei Tan, Ajay Kumar Pathak

Research output: Journal article publicationJournal articleAcademic researchpeer-review

106 Citations (Scopus)

Abstract

Online iris recognition using distantly acquired images in a less imaging constrained environment requires the development of a efficient iris segmentation approach and recognition strategy that can exploit multiple features available for the potential identification. This paper presents an effective solution toward addressing such a problem. The developed iris segmentation approach exploits a random walker algorithm to efficiently estimate coarsely segmented iris images. These coarsely segmented iris images are postprocessed using a sequence of operations that can effectively improve the segmentation accuracy. The robustness of the proposed iris segmentation approach is ascertained by providing comparison with other state-of-the-art algorithms using publicly available UBIRIS.v2, FRGC, and CASIA.v4-distance databases. Our experimental results achieve improvement of 9.5%, 4.3%, and 25.7% in the average segmentation accuracy, respectively, for the UBIRIS.v2, FRGC, and CASIA.v4-distance databases, as compared with most competing approaches. We also exploit the simultaneously extracted periocular features to achieve significant performance improvement. The joint segmentation and combination strategy suggest promising results and achieve average improvement of 132.3%, 7.45%, and 17.5% in the recognition performance, respectively, from the UBIRIS.v2, FRGC, and CASIA.v4-distance databases, as compared with the related competing approaches.
Original languageEnglish
Article number6508951
Pages (from-to)3751-3765
Number of pages15
JournalIEEE Transactions on Image Processing
Volume22
Issue number10
DOIs
Publication statusPublished - 9 Sep 2013

Keywords

  • Identification at-a-distance
  • Iris Recognition
  • Iris Segmentation
  • Periocular Recognition
  • Remote Biometrics

ASJC Scopus subject areas

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

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