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Red-Channel Based Iris Segmentation for Pupil Detection

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The 3rd International Conference on Artificial Intelligence and Computer Vision (AICV2023), March 5–7, 2023 (AICV 2023)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 164))

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Abstract

Iridology is the science and practice that helps to learn the health status through the examination of the structural aspects of an eye. Iris segmentation is an important phase in Iridology that aids to recognize iris signs and identify aberrant organ activity. The primary elements of iris segmentation are the detections of the iris and pupil. However, iris segmentation is greatly impacted by noises and images with low quality. The proper method for iris and pupil detection supports improving the result of iris segmentation in Iridology. This study provides a computer vision-based method to segment the human eye’s iris and pupil using an alternate method. The procedure is based on the red channel information of the image with various image processing operations. Iris images from the UBIRIS.v1. Dataset, which was taken in less restrictive image acquisition conditions, is used in an experiment. This method gives a unique way for iris segmentation with an accuracy of 97.49%.

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Acknowledgment

This work has been supported by the Centre for Machine Learning and Intelligence (CMLI) funded by the Department of Science and Technology (DST-CURIE).

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Authors and Affiliations

  1. Department of Computer Science, Centre for Machine Learning and Intelligence (CMLI) Avinashilingam Institute, Coimbatore, India

    S. Bhuvaneswari & P. Subashini

Authors
  1. S. Bhuvaneswari
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  2. P. Subashini
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Corresponding author

Correspondence to S. Bhuvaneswari .

Editor information

Editors and Affiliations

  1. Faculty of Computer and AI, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

  2. Faculty of Sciences and Techniques, Hassan 1st University, Settat, Morocco

    Abdelkrim Haqiq

  3. College of Computer and Information Sciences, Prince Sultan University, Riyadh, Saudi Arabia

    Ahmad Taher Azar

  4. Department of Computer Science, University of South Dakota, Vermillion, SD, USA

    KC Santosh

  5. Vardhaman College of Engineering, Hyderabad, Telangana, India

    M. A. Jabbar

  6. Department of Electronics and Computer Science, Koszalin University of Technology, Koszalin, Poland

    Adam Słowik

  7. Department of Computer Science, Avinashilingam University for Women, Coimbatore, Tamil Nadu, India

    Parthasarathy Subashini

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Bhuvaneswari, S., Subashini, P. (2023). Red-Channel Based Iris Segmentation for Pupil Detection. In: Hassanien, A.E., et al. The 3rd International Conference on Artificial Intelligence and Computer Vision (AICV2023), March 5–7, 2023. AICV 2023. Lecture Notes on Data Engineering and Communications Technologies, vol 164. Springer, Cham. https://doi.org/10.1007/978-3-031-27762-7_22

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