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Robust encoding of local ordinal measures: A general framework of iris recognition

  • Zhenan Sun*
  • , Tieniu Tan
  • , Yunhong Wang
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

The randomness of iris pattern makes it one of the most reliable biometric traits. On the other hand, the complex iris image structure and various sources of intra-class variations result in the difficulty of iris representation. Although diverse iris recognition methods have been proposed, the fundamentals of iris recognition have not a unified answer. As a breakthrough of this problem, we found that several accurate iris recognition algorithms share a same idea - local ordinal encoding, which is the representation well-suited for iris recognition. After further analysis and summarization, a general framework of iris recognition is formulated in this paper. This work discovered the secret of iris recognition. With the guidance of this framework, a novel iris recognition method based on robust estimating the direction of image gradient vector is developed. Extensive experimental results demonstrate our idea.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsDavide Maltoni, Anil K. Jain
PublisherSpringer Verlag
Pages270-282
Number of pages13
ISBN (Print)3540224998, 9783540224990
DOIs
StatePublished - 2004
Externally publishedYes

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3087
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

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