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A robust iris localization scheme for the iris recognition

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Abstract

Due to current security situations around the globe, iris biometric technology is highly preferred for both overt and covert applications. A typical iris biometric system includes image acquisition, iris segmentation, features extraction, and matching and recognition modules. Amongst these modules, iris segmentation plays a decisive role because it segments the valid iris part in an input eyeimage. It includes two tasks: iris localization and noise (e.g., eyelids) removal. Notably, the overall performance of an iris biometric system strongly relies on the iris localization task, because it demarcates the actual iris contours. Some contemporary iris localization schemes search over a three-dimensional (3D) space while marking iris boundaries, which is a time-consuming process if not optimized properly. Besides, some schemes also resort to the fixed and/or crude thresholding-based techniques for pupil localization. Notably, such schemes may perform poorly if image data do not maintain quality. To address these issues, this study proposes a robust iris localization scheme maintaining both speed and accuracy. It includes preprocessing the input eyeimage using an order statistic-filter and the bilinear interpolation scheme, extracting an adaptive threshold using the image’s histogram, processing binary image via the morphological operators, extracting pupil’s center and radius based on the centroid and geometry concepts, marking iris outer boundary using the Circular Hough transform (CHT) and refining coarse iris boundaries through the Fourier series. The proposed scheme exhibits relatively better experimental results compared with some contemporary iris localization schemes on the public iris databases: IITD V1.0, CASIA-Iris-Interval and MMU V1.0.

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Acknowledgments

Authors are thankful to the Malaysia Multimedia University (MMU), Department of Computer Science SOCIA Lab. Malaysia; the Biometrics Research Laboratory, Indian Institute of Technology Delhi (IITD), New Delhi, India; and the Chinese Academy of Sciences’ Institute of Automation (CASIA) for granting us free access to their relevant iris databases.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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Authors and Affiliations

  1. Department of Computer Science, College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam, Saudi Arabia

    Farmanullah Jan, Nasro Min-Allah & Irfanullah Khan

  2. Department of Electrical and Computer Engineering, COMSATS University Islamabad, Park Road, Chak Shahzad, Islamabad, 44000, Pakistan

    Shahrukh Agha

  3. Department of Computer Science, College of Computing and Informatics, Saudi Electronic University, Riyadh, Saudi Arabia

    Imran Usman

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  1. Farmanullah Jan
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  2. Nasro Min-Allah
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  3. Shahrukh Agha
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  4. Imran Usman
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  5. Irfanullah Khan
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Correspondence to Farmanullah Jan.

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Jan, F., Min-Allah, N., Agha, S. et al. A robust iris localization scheme for the iris recognition. Multimed Tools Appl 80, 4579–4605 (2021). https://doi.org/10.1007/s11042-020-09814-5

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  • DOI: https://doi.org/10.1007/s11042-020-09814-5

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