Iris tissue recognition based on GLDM feature extraction and hybrid MLPNN-ICA classifier

被引：36
|
作者：
Ahmadi, Neda [1 ]
Akbarizadeh, Gholamreza [2 ]
机构：
[1] Shahid Chamran Univ Ahvaz, Fac Engn, Dept Comp Engn, Ahvaz, Iran
[2] Shahid Chamran Univ Ahvaz, Fac Engn, Dept Elect Engn, Ahvaz, Iran
来源：
NEURAL COMPUTING & APPLICATIONS | 2020年 / 32卷 / 07期
关键词：
Iris tissue recognition; Feature extraction; GLDM; Imperialist competitive algorithm; Multi-layer perceptron neural network; SEGMENTATION; FRAMEWORK;
D O I：
10.1007/s00521-018-3754-0
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The use of iris tissue for identification is an accurate and reliable system for identifying people. This method consists of four main processing stages, namely segmentation, normalization, feature extraction, and matching. In this study, a new method of feature extraction and classification based on gray-level difference method and hybrid MLPNN-ICA classifier is proposed. For experimental results, our study is implemented on CASIA-Iris V3 dataset and UCI machine learning repository datasets.
引用
收藏
页码：2267 / 2281
页数：15
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