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Iris Segmentation Using Improved Hough Transform

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Emerging Intelligent Computing Technology and Applications (ICIC 2012)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 304))

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Abstract

This paper presents an efficient iris segmentation algorithm. This paper uses an improved circular Hough transform to detect inner boundary and the circular integro-differential operator to detect the outer boundary of iris from a given eye image. Search space of the standard circular Hough transform is reduced from three dimensions to only one dimension, which is the radius. Local gradient information is used to improve time and efficiency of Hough transform. This algorithm has been tested on the publicly available CASIA 3.0 Interval database consisting of 2639 images of 249 subjects and CASIA 4.0 Lamp database consisting of 16,212 images of 411 subjects. It also provides error categorization for wrong segmentation, as well as a study on parametric influences on error. Parameterized error analysis helps to set parameters intelligently boosting up the segmentation accuracy as high as 99.8% on the Interval database and 99.7% on the Lamp database.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Indian Institute of Technology Kanpur, Kanpur, 208016, India

    Amit Bendale, Aditya Nigam, Surya Prakash & Phalguni Gupta

Authors
  1. Amit Bendale
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  2. Aditya Nigam
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  3. Surya Prakash
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  4. Phalguni Gupta
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Editor information

Editors and Affiliations

  1. Machine Learning and Systems Biology Laboratory, School of Electronics and Information Engineering, Tongji University, Shanghai, China

    De-Shuang Huang

  2. Department of Computer Science and Engineering, Indian Institute of Technology Kanpur, 208016, Kanpur, India

    Phalguni Gupta

  3. Department of Chemistry, University of Louisville, 2320 South Brook Street, 40292, Louisville, Kentucky, USA

    Xiang Zhang

  4. School of Electrical, Computer & Telecommunications Engineering, The University of Wollongong,, 2522, North Wollongong, NSW, Australia

    Prashan Premaratne

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© 2012 Springer-Verlag Berlin Heidelberg

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Bendale, A., Nigam, A., Prakash, S., Gupta, P. (2012). Iris Segmentation Using Improved Hough Transform. In: Huang, DS., Gupta, P., Zhang, X., Premaratne, P. (eds) Emerging Intelligent Computing Technology and Applications. ICIC 2012. Communications in Computer and Information Science, vol 304. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31837-5_59

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  • DOI: https://doi.org/10.1007/978-3-642-31837-5_59

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31836-8

  • Online ISBN: 978-3-642-31837-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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