Iris recognition using artificial neural networks

被引：39
|
作者：
Sibai, Fadi N. [1 ]
Hosani, Hafsa I. [1 ]
Naqbi, Raja M. [1 ]
Dhanhani, Salima [1 ]
Shehhi, Shaikha [1 ]
机构：
[1] UAE Univ, Fac Informat Technol, Al Ain, U Arab Emirates
来源：
EXPERT SYSTEMS WITH APPLICATIONS | 2011年 / 38卷 / 05期
关键词：
Iris recognition; Feedforward neural networks; Backpropagation training algorithm; Image data partitioning techniques;
D O I：
10.1016/j.eswa.2010.11.029
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Biometrics recognition is one of the leading identity recognition means in the world today. Iris recognition is very effective for person identification due to the iris' unique features and the protection of the iris from the environment and aging. This paper presents a simple methodology for pre-processing iris images and the design and training of a feedforward artificial neural network for iris recognition. Three different iris image data partitioning techniques and two data codings are proposed and explored. Brain-Maker simulations reveal that recognition accuracies as high as 93.33% can be reached despite our testing of similar irises of the same color. We also experiment with various number of hidden layers, number of neurons in each hidden layer, input format (binary vs. analog), percent of data used for training vs testing, and with the addition of noise. Our recognition system achieves high accuracy despite using simple data pre-processing and a simple neural network. (C) 2010 Elsevier Ltd. All rights reserved.
引用
收藏
页码：5940 / 5946
页数：7
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