Convolutional neural network-based finger vein recognition using near infrared images
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...
| Main Authors: | , , , |
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| Format: | Proceeding Paper |
| Language: | English English |
| Published: |
IEEE
2018
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/67953/ http://irep.iium.edu.my/67953/7/67953%20%20Convolutional%20Neural%20Network-based.pdf http://irep.iium.edu.my/67953/13/67953%20%20Convolutional%20Neural%20Network-based_Scopus.pdf |
| _version_ | 1848786858715119616 |
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| author | Fairuz, Subha Habaebi, Mohamed Hadi Elsheikh, Elsheikh Mohamed Ahmed Chebil, Jalel |
| author_facet | Fairuz, Subha Habaebi, Mohamed Hadi Elsheikh, Elsheikh Mohamed Ahmed Chebil, Jalel |
| author_sort | Fairuz, Subha |
| building | IIUM Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T17:15:43Z |
| format | Proceeding Paper |
| id | iium-67953 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-14T17:15:43Z |
| publishDate | 2018 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | iium-679532019-08-17T03:38:28Z http://irep.iium.edu.my/67953/ Convolutional neural network-based finger vein recognition using near infrared images Fairuz, Subha Habaebi, Mohamed Hadi Elsheikh, Elsheikh Mohamed Ahmed Chebil, Jalel TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices 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. IEEE 2018-11 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/67953/7/67953%20%20Convolutional%20Neural%20Network-based.pdf application/pdf en http://irep.iium.edu.my/67953/13/67953%20%20Convolutional%20Neural%20Network-based_Scopus.pdf 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. https://ieeexplore.ieee.org/document/8539342 10.1109/ICCCE.2018.8539342 |
| spellingShingle | TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices Fairuz, Subha Habaebi, Mohamed Hadi Elsheikh, Elsheikh Mohamed Ahmed Chebil, Jalel Convolutional neural network-based finger vein recognition using near infrared images |
| title | Convolutional neural network-based finger vein
recognition using near infrared images |
| title_full | Convolutional neural network-based finger vein
recognition using near infrared images |
| title_fullStr | Convolutional neural network-based finger vein
recognition using near infrared images |
| title_full_unstemmed | Convolutional neural network-based finger vein
recognition using near infrared images |
| title_short | Convolutional neural network-based finger vein
recognition using near infrared images |
| title_sort | convolutional neural network-based finger vein
recognition using near infrared images |
| topic | TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices |
| url | http://irep.iium.edu.my/67953/ http://irep.iium.edu.my/67953/ http://irep.iium.edu.my/67953/ http://irep.iium.edu.my/67953/7/67953%20%20Convolutional%20Neural%20Network-based.pdf http://irep.iium.edu.my/67953/13/67953%20%20Convolutional%20Neural%20Network-based_Scopus.pdf |