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International Conference on Contemporary Computing

IC3 2009: Contemporary Computing pp 295–306Cite as

CDIS: Circle Density Based Iris Segmentation

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 40))

Abstract

Biometrics is an automated approach of measuring and analysing physical and behavioural characteristics for identity verification. The stability of the Iris texture makes it a robust biometric tool for security and authentication purposes. Reliable Segmentation of Iris is a necessary precondition as an error at this stage will propagate into later stages and requires proper segmentation of non-ideal images having noises like eyelashes, etc. Iris Segmentation work has been done earlier but we feel it lacks in detecting iris in low contrast images, removal of specular reflections, eyelids and eyelashes. Hence, it motivates us to enhance the said parameters. Thus, we advocate a new approach CDIS for Iris segmentation along with new algorithms for removal of eyelashes, eyelids and specular reflections and pupil segmentation. The results obtained have been presented using GAR vs. FAR graphs at the end and have been compared with prior works related to segmentation of iris.

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Author information

Authors and Affiliations

  1. Department of Information Technology, Netaji Subhas Institute of Technology, Delhi University, New Delhi, India

    Anand Gupta, Anita Kumari, Boris Kundu & Isha Agarwal

Authors
  1. Anand Gupta
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  2. Anita Kumari
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  3. Boris Kundu
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  4. Isha Agarwal
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Editor information

Editors and Affiliations

  1. Dept. of Computer Sciences, University of Florida, Gainesville, FL, 32611, USA

    Sanjay Ranka

  2. Laurence H. Baker Center for Bioinformatics and Biological Statistics, Iowa State University, USA

    Srinivas Aluru

  3. Grid Computing and Distributed Systems Laboratory and, NICTA Victoria Laboratory, Department of Computer Science and Software Engineering, The University of Melbourne, Australia

    Rajkumar Buyya

  4. Department of Computer Science, National Tsing Hua University, Taiwan

    Yeh-Ching Chung

  5. Computer Science, College of Engineering and Science, Louisiana Tech University, Ruston, LA, 71272, USA

    Sumeet Dua  & Vir V. Phoha  & 

  6. Department of Computer Sciences, Purdue University, W. Lafayette, IN, 47907, USA

    Ananth Grama

  7. Arizona State University, Tempe, AZ, 85281, USA

    Sandeep K. S. Gupta

  8. Computer Science and Engineering Department, Indian Institute of Technology Kharagpur, 721 302, WB, India

    Rajeev Kumar

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© 2009 Springer-Verlag Berlin Heidelberg

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Cite this paper

Gupta, A., Kumari, A., Kundu, B., Agarwal, I. (2009). CDIS: Circle Density Based Iris Segmentation. In: Ranka, S., et al. Contemporary Computing. IC3 2009. Communications in Computer and Information Science, vol 40. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03547-0_28

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  • DOI: https://doi.org/10.1007/978-3-642-03547-0_28

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-03546-3

  • Online ISBN: 978-3-642-03547-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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