Sparsity inspired selection and recognition of iris images

Jaishanker K. Pillai, Vishal M. Patel, Rama Chellappa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

28 Scopus citations

Abstract

Iris images acquired from a partially cooperating subject often suffer from blur, occlusion due to eyelids, and specular reflections. The performance of existing iris recognition systems degrade significantly on these images. Hence it is essential to select good images from the incoming iris video stream, before they are input to the recognition algorithm. In this paper, we propose a sparsity based algorithm for selection of good iris images and their subsequent recognition. Unlike most existing algorithms for iris image selection, our method can handle segmentation errors and a wider range of acquisition artifacts common in iris image capture. We perform selection and recognition in a single step which is more efficient than devising separate specialized algorithms for the two. Recognition from partially cooperating users is a significant step towards deploying iris systems in a wide variety of applications.

Original languageEnglish (US)
Title of host publicationIEEE 3rd International Conference on Biometrics
Subtitle of host publicationTheory, Applications and Systems, BTAS 2009
DOIs
StatePublished - 2009
Externally publishedYes
EventIEEE 3rd International Conference on Biometrics: Theory, Applications and Systems, BTAS 2009 - Washington, DC, United States
Duration: Sep 28 2009Sep 30 2009

Publication series

NameIEEE 3rd International Conference on Biometrics: Theory, Applications and Systems, BTAS 2009

Other

OtherIEEE 3rd International Conference on Biometrics: Theory, Applications and Systems, BTAS 2009
Country/TerritoryUnited States
CityWashington, DC
Period9/28/099/30/09

All Science Journal Classification (ASJC) codes

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

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