New full Iris Recognition System and Iris Segmentation Technique Using Image Processing and Deep Convolutional Neural Network

Omar Medhat Moslhi¹

1. ARAB Academy for Science Technology and Maritime Transport, Giza, 32817, Egypt.

Section:Research Paper, Product Type: Journal-Paper
Vol.6 , Issue.3 , pp.20-27, Mar-2020

Online published on Mar 30, 2020

Copyright © Omar Medhat Moslhi . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
Iris recognition is a technology used in many security systems. Irises are different among all people every person has a unique iris shape and there is no two irises have the same format. In this paper, a new model is introduced in iris recognition to make this technology easy for anyone to use it, especially that any image can be used in the model and the model filter itself and choose only the images that pass the model filters. This paper presents an iris recognition system from the beginning of eye detection to the end of recognizing the iris images. This paper also presents a new process to make iris recognition which is a blend between image processing techniques with deep learning to make iris Recognition. Also, this paper represents a new iris segmentation technique that detects the iris images efficiently with high accuracy. The iris recognition model is beginning an eye detection process then the iris detection process takes place which detects the iris inside the eyes then iris segmentation process gets iris images that will be saved and used in the last process which is responsible for iris classification using convolutional neural network. The iris recognition system was tested on well-known data sets: Casia Iris-Thousand, Casia Iris Interval, Ubiris Version 1 (v1) and Ubiris Version 2 (v2).

Key-Words / Index Term :
Iris Recognition, Iris Segmentation, Computer Vision, Convolutional Neural Network, Image Processing

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