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Robust Encoding of Local Ordinal Measures: A General Framework of Iris Recognition

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Biometric Authentication (BioAW 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3087))

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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.

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Authors and Affiliations

  1. Center for Biometrics Authentication and Testing National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, P.O. Box 2728, Beijing, 100080, P.R. China

    Zhenan Sun, Tieniu Tan & Yunhong Wang

Authors
  1. Zhenan Sun
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  2. Tieniu Tan
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  3. Yunhong Wang
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Editor information

Editors and Affiliations

  1. Biometric System Laboratory, DEIS, University of Bologna, via Sacchi 3, 47023, Cesena, Italy

    Davide Maltoni

  2. Department of Computer Science and Engineering, Michigan State University,  

    Anil K. Jain

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© 2004 Springer-Verlag Berlin Heidelberg

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Sun, Z., Tan, T., Wang, Y. (2004). Robust Encoding of Local Ordinal Measures: A General Framework of Iris Recognition. In: Maltoni, D., Jain, A.K. (eds) Biometric Authentication. BioAW 2004. Lecture Notes in Computer Science, vol 3087. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-25976-3_25

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  • DOI: https://doi.org/10.1007/978-3-540-25976-3_25

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22499-0

  • Online ISBN: 978-3-540-25976-3

  • eBook Packages: Springer Book Archive

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