Iris Recognition using a Novel Segmentation Method and Fuzzy ARTMAP Neural Network

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  • Arash Taherian1,
  • Mahdi Aliyari Sh.2,
  1. Department of Electrical and Computer Engineering, Islamic Azad University, South Tehran Branch, Tehran
  2. Faculty of Electrical and Computer Engineering, K. N. Toosi University of Technology, Tehran

Published in Issue 2024-02-25

How to Cite

Taherian, A., & Aliyari Sh., M. (2024). Iris Recognition using a Novel Segmentation Method and Fuzzy ARTMAP Neural Network. Majlesi Journal of Electrical Engineering, 7(1). https://oiccpress.com/mjee/article/view/5231

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Abstract

A biometric system provides automatic identification of an individual based on unique features or characteristics possessed by that person. Iris recognition is regarded as one of the most reliable and accurate biometric systems available. This paper, proposes an efficient iris recognition system that employs a novel method to localize the iris region in the eye image based on approximating the iris radius using the pupil characteristics and cumulative SUM based gray change analysis to extract features from the normalized iris template and also Fuzzy ARTMAP neural network to classify the iris codes. The results of simulations on a set of 756 eye images illustrate that a fast, accurate and noise resistant personal identification system has been successfully designed. The proposed system achieved 0 false acceptance rate using 1800-bit binary iris codes and recognized all authorized users with 100% accuracy.

Keywords

  • Clustering Error. Dataset,
  • Fuzz y ARTMAP Neural Network,
  • iris recognition,
  • Segmentation
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