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Fast Iris Segmentation Algorithm for Visible Wavelength Images Based on Multi-color Space

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Book cover Advanced Concepts for Intelligent Vision Systems (ACIVS 2020)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 12002))

Abstract

Iris recognition for eye images acquired in visible wavelength is receiving increasing attention. In visible wavelength environments, there are many factors that may cover or affect the iris region which makes the iris segmentation step more difficult and challenging. In this paper, we propose a novel and fast segmentation algorithm to deal with eye images acquired in visible wavelength environments by considering the color information form multiple color spaces. The various existing color spaces such as RGB, YCbCr, and HSV are analyzed and an appropriate set of color models is selected for the segmentation process. To accurately localize the iris region, a set of convenient techniques are applied to detect and remove the non-iris regions such as pupil, specular reflection, eyelids, and eyelashes. Our experimental results and comparative analysis using the UBIRIS v2 database demonstrate the efficiency of our approach in terms of segmentation accuracy and execution time.

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Author information

Authors and Affiliations

  1. Fatih Sultan Mehmet Vakif University, Istanbul, Turkey

    Shaaban Sahmoud

  2. Mosul University, Mosul, Iraq

    Hala N. Fathee

Authors
  1. Shaaban Sahmoud
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  2. Hala N. Fathee
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Corresponding author

Correspondence to Shaaban Sahmoud .

Editor information

Editors and Affiliations

  1. DGA, Paris, France

    Jacques Blanc-Talon

  2. University of Auckland, Auckland, New Zealand

    Patrice Delmas

  3. Ghent University, Ghent, Belgium

    Wilfried Philips

  4. CSIRO, Canberra, Australia

    Dan Popescu

  5. University of Antwerp, Wilrijk, Belgium

    Paul Scheunders

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Sahmoud, S., Fathee, H.N. (2020). Fast Iris Segmentation Algorithm for Visible Wavelength Images Based on Multi-color Space. In: Blanc-Talon, J., Delmas, P., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2020. Lecture Notes in Computer Science(), vol 12002. Springer, Cham. https://doi.org/10.1007/978-3-030-40605-9_21

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  • DOI: https://doi.org/10.1007/978-3-030-40605-9_21

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-40604-2

  • Online ISBN: 978-3-030-40605-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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