Volume 19, No. 1, 2022
Efficient Eye Recognition for Secure Systems Using Convolutional Neural Network
Ahmed Abdulrudah Abbass, Hussein Lafta Hussein, Wisam Abed Shukur, Jasim Kaabi and Robert Tornai
Abstract
Individual’s eye recognition is an important issue in applications such as security systems, credit card control and guilty identification. Using video images cause to destroy the limitation of fixed images and to be able to receive users’ image under any condition as well as doing the eye recognition. There are some challenges in these systems; changes of individual gestures, changes of light, face coverage, low quality of video images and changes of personal characteristics in each frame. There is a need for two phases in order to do the eye recognition using images; revelation and eye recognition which will use in the security systems to identify the persons. The main aim of this paper is innovation in eye recognition phase. In this paper, a new and fast method is proposed for human eye recognition that can quickly specify the human eye location in an input image. In the proposed method, eyes will be specified in an input image with a CNN neural network. This proposed method is tested on different images and provided highest accuracy for the image recognition which used in security systems.
Pages: 4967-4978
DOI: 10.14704/WEB/V19I1/WEB19333
Keywords: Eye Recognition, Information Security, Identification, Iris Features, Biometry, Convolutional Neural Network