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All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
M. Timouyas
Mohammed V University
Computer Science & IT Engineering

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Iris segmentation using a new unsupervised neural approach Hicham Ohmaid; S. Eddarouich; A. Bourouhou; M. Timouyas
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 9, No 1: March 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (642.383 KB) | DOI: 10.11591/ijai.v9.i1.pp58-64

Abstract

A biometric system of identification and authentication provides automatic recognition of an individual based on certain unique features or characteristic possessed by an individual. Iris recognition is a biometric identification method that uses pattern recognition on the images of the iris. Owing to the unique epigenetic patterns of the iris, Iris recognition is considered as one of the most accurate methods in the field of biometric identification. One of the crucial steps in the iris recognition system is the iris segmentation because it significantly affects the accuracy of the feature extraction the iris. The segmentation algorithm proposed in this article starts with determining the regions of the eye using unsupervised neural approach, after the outline of the eye is found using the Canny edge, The Hough Transform is employed to determine the center and radius of the pupil and the iris.
Co-Authors A. Bourouhou Hicham Ohmaid S. Eddarouich