IIUM Repository (IREP)

Convolutional neural network-based finger vein recognition using near infrared images

Fairuz, Subha and Habaebi, Mohamed Hadi and Elsheikh, Elsheikh Mohamed Ahmed and Chebil, Jalel (2018) Convolutional neural network-based finger vein recognition using near infrared images. In: 2018 7th International Conference on Computer Communication Engineering (ICCCE2018), 19th-20th September 2018, Kuala Lumpur.

[img] PDF - Published Version
Restricted to Registered users only

Download (1MB) | Request a copy
[img]
Preview
PDF (scopus) - Supplemental Material
Download (291kB) | Preview

Abstract

Convolutional Neural Network (CNN) is opening new horizons in biometrics-based authentication field and finger vein recognition is the prominent one which can provide the best possible security system depending on this aforementioned technology. In this paper, we used 5 convolutional layers and 4 fully-connected layers where our developed network has shown the capability to produce the result with almost 100% accuracy rate which became possible due to the fact that deep learning, an end-to-end system is used which performs better in a lot of aspects in comparison to conventional techniques.Convolutional Neural Network (CNN) is opening new horizons in biometrics-based authentication field and finger vein recognition is the prominent one which can provide the best possible security system depending on this aforementioned technology. In this paper, we used 5 convolutional layers and 4 fully-connected layers where our developed network has shown the capability to produce the result with almost 100% accuracy rate which became possible due to the fact that deep learning, an end-to-end system is used which performs better in a lot of aspects in comparison to conventional techniques.

Item Type: Conference or Workshop Item (Plenary Papers)
Additional Information: 6727/67953
Uncontrolled Keywords: deep learning, convolutional neural network, finger vein recognition, energy security, biometric, NIR
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices
Kulliyyahs/Centres/Divisions/Institutes: Kulliyyah of Engineering
Kulliyyah of Engineering > Department of Electrical and Computer Engineering
Depositing User: Dr. Mohamed Hadi Habaebi
Date Deposited: 06 Dec 2018 08:44
Last Modified: 17 Aug 2019 11:38
URI: http://irep.iium.edu.my/id/eprint/67953

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year