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Neural Computing and Applications
Erschienen in: Neural Computing and Applications 7/2020

04.10.2018 | Original Article

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

verfasst von: Neda Ahmadi, Gholamreza Akbarizadeh

Erschienen in: Neural Computing and Applications | Ausgabe 7/2020

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Abstract

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.
Vorheriger Artikel Design of active noise control system using hybrid functional link artificial neural network and finite impulse response filters
Nächster Artikel A machine learning approach for prediction of pregnancy outcome following IVF treatment

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Metadaten
Titel
Iris tissue recognition based on GLDM feature extraction and hybrid MLPNN-ICA classifier
verfasst von
Neda Ahmadi
Gholamreza Akbarizadeh
Publikationsdatum
04.10.2018
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 7/2020
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-018-3754-0

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