Neural Network Approach to Iris Recognition in Noisy Environment

被引：14

作者：

Hajari, Kamal ^{[1
]}

Gawande, Ujwalla ^{[1
]}

Golhar, Yogesh ^{[1
]}

机构：

[1] YCCE, Dept Informat Technol, Nagpur 441110, Maharashtra, India

来源：

1ST INTERNATIONAL CONFERENCE ON INFORMATION SECURITY & PRIVACY 2015 | 2016年 / 78卷

关键词：

Noisy environment; Noisy Artifacts; Occlusion; Local Binary Pattern; Iris Recognition; Neural Networks; BIOMETRICS;

D O I：

10.1016/j.procs.2016.02.116

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Iris recognition is a challenging problem in the noisy environment. Our primary focus is to develop the reliable iris recognition system that can work in a noisy imaging environment and to increase the iris recognition rate on CASIA and MMUiris datasets. This research paper proposes two algorithms, first, a novel method for removing noise from the iris image and second, a texture feature extraction method using a combined approach of Local Binary Pattern (LBP) and Gray Level Co-occurrence Matrix (GLCM). Our proposed approach give highest recognition rate of 96.5% and low error rate and requires less execution time. (C) 2016 The Authors. Published by Elsevier B.V.

引用

页码：675 / 682

页数：8

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