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Iris segmentation for non-ideal Iris biometric systems

  • 1158T: Role of Computer Vision in Smart Cities: Applications and Research Challenges
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Abstract

At present, iris recognition systems are highly demanded for covert applications such as monitoring terrorist activities at public places, walk-through portals, smart cities, etc. In general, these systems use image acquisition setups working under relaxed conditions due to which the quality of acquired images is usually poor. For example, images may contain non-uniform illumination, defocus, blur, reflections and eyelids/eyelashes occlusion. Due to these issues, most contemporary iris segmentation schemes do not perform well. In addition, precise localization of eyes in human face images is also a challenging task. No doubt, wrong localization of eyes may certainly lead to failure of the subsequent system modules. To contribute in this regard, this study offers a robust scheme that functions as follows. First, it supplements the Viola-Jones algorithm with the geometrical information of human face to segment eyes. Next, it preprocesses an eyeimage to enhance its contrast, suppress reflections, smooth down spiky gray-level variations if any and marks a circular region-of-interest (ROI) containing iris. Then, it applies an iterative scheme involving Hough transform to segment iris. Finally, it extracts non-circular iris contours using an effective scheme centered on the Lagrange interpolating polynomial. This scheme has shown improved performance on public face-dataset (CASIA-IrisV4-Distance) and two iris datasets, MMU V1.0 and IITD V1.0. On average, it attained 97.97% accuracy rate on these databases.

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Acknowledgments

Authors are thankful to the Deanship of Scientific Research (DSR), Imam Abdulrahman Bin Faisal University (IAU) for generous funding. Authors are also thankful to the Chinese Academy of Sciences and Malaysia Multimedia University whose iris databases have been utilized in this study.

Funding

The Deanship of Scientific Research (DSR), Imam Abdulrahman Bin Faisal University (IAU) has funded this study under project numbered 2019–359-CSIT.

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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

  2. Management Information Systems Department, College of Applied Studies and Community Service, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam, Saudi Arabia

    Saleh Alrashed

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  1. Farmanullah Jan
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Correspondence to Farmanullah Jan.

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Jan, F., Alrashed, S. & Min-Allah, N. Iris segmentation for non-ideal Iris biometric systems. Multimed Tools Appl 83, 15223–15251 (2024). https://doi.org/10.1007/s11042-021-11075-9

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