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Iris Recognition Using Localized Zernike Features with Partial Iris Pattern

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New Trends in Information and Communications Technology Applications (NTICT 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1183))

Abstract

Iris recognition is an attractive field of research for the purpose of identifying people based on unique patterns extracted from their iris. Accurate iris recognition requires high quality of iris images with the most discriminating features and minimum variation level. Analyzing and encoding of an iris image captured by a real (i.e., non-ideal) imaging system is a crucial issue. This paper presents a new iris pattern for human identification; i.e., partial iris pattern, instead of the whole iris. Then, a feature-set consisting of Gabor and Zernike moments is used for feature extraction and matching. The features are calculated to the ninth order. Two datasets are used for testing and evaluating the proposed technique. The experiential results show that the proposed technique is reliable, promising, and can be applied in real world imaging systems.

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Author information

Authors and Affiliations

  1. Department of Postgraduate Studies, University of Information Technology and Communications, Baghdad, Iraq

    Sinan A. Naji

  2. Doctoral School of Informatics, Faculty of Informatics, University of Debrecen, Debrecen, Hungary

    Robert Tornai & Jasim H. Lafta

  3. Department of Computer Science, Ibn Al-Haitham College of Education for Pure Sciences, University of Baghdad, Baghdad, Iraq

    Hussein L. Hussein

Authors
  1. Sinan A. Naji
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  2. Robert Tornai
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  3. Jasim H. Lafta
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  4. Hussein L. Hussein
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Corresponding author

Correspondence to Sinan A. Naji .

Editor information

Editors and Affiliations

  1. University of Information Technology and Communications, Baghdad, Iraq

    Abbas M. Al-Bakry

  2. University of Information Technology and Communications, Baghdad, Iraq

    Safaa O. Al-Mamory

  3. University of Information Technology and Communications, Baghdad, Iraq

    Mouayad A. Sahib

  4. University of Information Technology and Communications, Baghdad, Iraq

    Haitham S. Hasan

  5. Open University of Tanzania, Dar es Salaam, Tanzania

    George S. Oreku

  6. University of Information Technology and Communications, Baghdad, Iraq

    Thaker M. Nayl

  7. University of Information Technology and Communications, Baghdad, Iraq

    Jaafar A. Al-Dhaibani

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Naji, S.A., Tornai, R., Lafta, J.H., Hussein, H.L. (2020). Iris Recognition Using Localized Zernike Features with Partial Iris Pattern. In: Al-Bakry, A., et al. New Trends in Information and Communications Technology Applications. NTICT 2020. Communications in Computer and Information Science, vol 1183. Springer, Cham. https://doi.org/10.1007/978-3-030-55340-1_16

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  • DOI: https://doi.org/10.1007/978-3-030-55340-1_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-55339-5

  • Online ISBN: 978-3-030-55340-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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