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103276

Noisy Iris Recognition Based on Deep Neural Network

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Last updated: 25 Dec 2024

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Abstract

Iris recognition is one of the Biometric systems used for persons identification based on their special iris traits, which are unique featuresfor each individual. It is clear that the progress in deep learning show how efficient the extracted features from convolutional neural networks (CNNs) to describe the complex image patterns. However, the influence of noise is a serious problem in most image processing systems. It may ariseto the iris recognition systems due to environmental conditions that can affects the features extracted from the iris images. Hence, the objective of this paper is to study the performance of CNNs based Deep learning (Alex net, Vgg16 and Vgg19) when used for iris recognition with the presence of noise and compares it with Masek algorithm. Simulation results reveal that using the deep learning greatly improves iris recognition accuracy for Alex CNN. We achieve 100%, 100%, 88.9% for interval, lamp and twins datasets respectively.

DOI

10.21608/mjeer.2020.103276

Authors

First Name

Eman M.

Last Name

Omran

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Affiliation

A National Center for Radiation Research and Technology (NCRRT), Egyptian Atomic Energy Authority (EAEA), Cairo 11787, Egypt.

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First Name

Randa F.

Last Name

Soliman

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Affiliation

Mathematics and Computer Science Department, Faculty of Science, Menoufia University, Shebin El-Koom, 32511, Egypt

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First Name

Maryam Mostafa

Last Name

Salah

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Mathematics and Computer Science Department, Faculty of Science, Menoufia University, Shebin El-Koom, 32511, Egypt

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First Name

Sameh A.

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Napoleon

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Affiliation

Mathematics and Computer Science Department, Faculty of Science, Menoufia University, Shebin El-Koom, 32511, Egypt

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First Name

El-Sayed M.

Last Name

El-Rabaie

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Affiliation

Electronics and Electrical Communications Engineering Department, Faculty of Electronic Engineering, Menouf 32951, Menoufia University.

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First Name

Mustafa M.

Last Name

AbdeElnaby

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Affiliation

Department of Electronics and Communications Engineering, Tanta University, Egypt

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First Name

Nabil A.

Last Name

Ismail

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Affiliation

Computer Science & Engineering Dept., Menoufia University, Egypt.

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First Name

Ayman A.

Last Name

Eisa

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-

Affiliation

A National Center for Radiation Research and Technology (NCRRT), Egyptian Atomic Energy Authority (EAEA), Cairo 11787, Egypt.

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Orcid

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First Name

Fathi

Last Name

abd El-samie

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-

Affiliation

Department of Electronics and Electrical Communications Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf 32952, Egypt

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Volume

29

Article Issue

2

Related Issue

15327

Issue Date

2020-07-01

Receive Date

2020-07-16

Publish Date

2020-07-01

Page Start

64

Page End

69

Print ISSN

1687-1189

Online ISSN

2682-3535

Article File

MJEER_Volume 29_Issue 2_Pages 64-69.pdf

PDF . 912.4kB

Link

https://mjeer.journals.ekb.eg/article_103276.html

Detail API

https://mjeer.journals.ekb.eg/service?article_code=103276

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8

Type

Original Article

Type Code

1,088

Publication Type

Journal

Publication Title

Menoufia Journal of Electronic Engineering Research

Publication Link

https://mjeer.journals.ekb.eg/

MainTitle

Noisy Iris Recognition Based on Deep Neural Network

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Article

Created At

22 Jan 2023