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Fast Iris Segmentation by Rotation Average Analysis of Intensity-Inversed Image

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Artificial Intelligence and Computational Intelligence (AICI 2009)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5855))

Abstract

Iris recognition is a reliable and accurate biometric technique used in modern personnel identification system. Segmentation of the effective iris region is the base of iris feature encoding and recognition. In this paper, a novel method is presented for fast iris segmentation. There are two steps to finish the iris segmentation. The first step is iris location, which is based on rotation average analysis of intensity-inversed image and non-linear circular regression. The second step is eyelid detection. A new method to detect the eyelids utilizing a simplified mathematical model of arc with three free parameters is implemented for quick fitting. Comparatively, the conventional model with four parameters is less optimal. Experiments were carried out on both self-collected images and CASIA database. The results show that our method is fast and robust in segmenting the effective iris region with high tolerance of noise and scaling.

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Author information

Authors and Affiliations

  1. Institute of Digital Lib., Zhejiang Sci-Tech University, Zhejiang, China

    Wei Li

  2. Department of BFSC, Leiden University, Leiden, The Netherlands

    Lin-Hua Jiang

Authors
  1. Wei Li
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  2. Lin-Hua Jiang
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Editor information

Editors and Affiliations

  1. School of Business Information Technology, RMIT University, City Campus, 124 La Trobe Street, 3000, Melbourne, Victoria, Australia

    Hepu Deng

  2. College of Metrological Technology and Engineering, China Jiliang University, 310018, Hangzhou, Zhejiang Province, China

    Lanzhou Wang

  3. Department of Computer Science, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon Tong, Hong Kong, China

    Fu Lee Wang

  4. College of Information Science and Technology, Hainan University, 570228, Haikou, China

    Jingsheng Lei

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© 2009 Springer-Verlag Berlin Heidelberg

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Li, W., Jiang, LH. (2009). Fast Iris Segmentation by Rotation Average Analysis of Intensity-Inversed Image. In: Deng, H., Wang, L., Wang, F.L., Lei, J. (eds) Artificial Intelligence and Computational Intelligence. AICI 2009. Lecture Notes in Computer Science(), vol 5855. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-05253-8_38

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  • DOI: https://doi.org/10.1007/978-3-642-05253-8_38

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-05252-1

  • Online ISBN: 978-3-642-05253-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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