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Iris feature extraction method based on LBP and chunked encoding

  • Yuqing He*
  • , Guangqin Feng
  • , Yushi Hou
  • , Li Li
  • , Evangelia Micheli-Tzanakou
  • *Corresponding author for this work
  • Ministry of Education in China
  • Rutgers - The State University of New Jersey, New Brunswick

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Iris feature extraction is a key issue in iris recognition. This paper proposes a novel iris feature extraction method based on local binary pattern (LBP) images and the chunked encoding method. Firstly it applies the LBP to the normalized iris image and obtains the iris' LBP image, then extracts the iris's feature via the chunked encoding method based on the iris' statistical information. Finally it completes the iris recognition and classification using Hamming distance. Experimental results showed that this algorithm can get higher recognition rate than the traditional iris feature extraction method, which demonstrated the efficiency of the proposed method.

Original languageEnglish
Title of host publicationProceedings - 2011 7th International Conference on Natural Computation, ICNC 2011
PublisherIEEE Computer Society
Pages1663-1667
Number of pages5
ISBN (Print)9781424499533
DOIs
Publication statusPublished - 2011
Externally publishedYes
Event2011 7th International Conference on Natural Computation, ICNC 2011 - Shanghai, China
Duration: 26 Jul 2011 → 28 Jul 2011

Publication series

NameProceedings - 2011 7th International Conference on Natural Computation, ICNC 2011
Volume3

Conference

Conference2011 7th International Conference on Natural Computation, ICNC 2011
Country/TerritoryChina
CityShanghai
Period26/07/11 → 28/07/11

Keywords

  • biometrics
  • chunked encoding
  • hamming distance
  • iris recognition
  • local binary pattern

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