Contact-Free Multispectral Identity Verification System Using Palm Veins and Deep Neural Network
Devices and systems secured by biometric factors became a part of our lives because they are convenient, easy to use, reliable, and secure. They use information about unique features of our bodies in order to authenticate a user. It is possible to enhance the security of these devices by adding supp...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2020-10-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/20/19/5695 |
| _version_ | 1797551672472371200 |
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| author | Maciej Stanuch Marek Wodzinski Andrzej Skalski |
| author_facet | Maciej Stanuch Marek Wodzinski Andrzej Skalski |
| author_sort | Maciej Stanuch |
| collection | DOAJ |
| description | Devices and systems secured by biometric factors became a part of our lives because they are convenient, easy to use, reliable, and secure. They use information about unique features of our bodies in order to authenticate a user. It is possible to enhance the security of these devices by adding supplementary modality while keeping the user experience at the same level. Palm vein systems are based on infrared wavelengths used for capturing images of users’ veins. It is both convenient for the user, and it is one of the most secure biometric solutions. The proposed system uses IR and UV wavelengths; the images are then processed by a deep convolutional neural network for extraction of biometric features and authentication of users. We tested the system in a verification scenario that consisted of checking if the images collected from the user contained the same biometric features as those in the database. The True Positive Rate (TPR) achieved by the system when the information from the two modalities were combined was 99.5% by the threshold of acceptance set to the Equal Error Rate (EER). |
| first_indexed | 2024-03-10T15:48:26Z |
| format | Article |
| id | doaj.art-12f8a0951ffc4fe29a15ac58c900d072 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T15:48:26Z |
| publishDate | 2020-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-12f8a0951ffc4fe29a15ac58c900d0722023-11-20T16:13:06ZengMDPI AGSensors1424-82202020-10-012019569510.3390/s20195695Contact-Free Multispectral Identity Verification System Using Palm Veins and Deep Neural NetworkMaciej Stanuch0Marek Wodzinski1Andrzej Skalski2Department of Measurement and Electronics, AGH University of Science and Technology, Al. Mickiewicza 30, 30-059 Krakow, PolandDepartment of Measurement and Electronics, AGH University of Science and Technology, Al. Mickiewicza 30, 30-059 Krakow, PolandDepartment of Measurement and Electronics, AGH University of Science and Technology, Al. Mickiewicza 30, 30-059 Krakow, PolandDevices and systems secured by biometric factors became a part of our lives because they are convenient, easy to use, reliable, and secure. They use information about unique features of our bodies in order to authenticate a user. It is possible to enhance the security of these devices by adding supplementary modality while keeping the user experience at the same level. Palm vein systems are based on infrared wavelengths used for capturing images of users’ veins. It is both convenient for the user, and it is one of the most secure biometric solutions. The proposed system uses IR and UV wavelengths; the images are then processed by a deep convolutional neural network for extraction of biometric features and authentication of users. We tested the system in a verification scenario that consisted of checking if the images collected from the user contained the same biometric features as those in the database. The True Positive Rate (TPR) achieved by the system when the information from the two modalities were combined was 99.5% by the threshold of acceptance set to the Equal Error Rate (EER).https://www.mdpi.com/1424-8220/20/19/5695biometricspalm vein scannermultimodalityconvolutional neural networks |
| spellingShingle | Maciej Stanuch Marek Wodzinski Andrzej Skalski Contact-Free Multispectral Identity Verification System Using Palm Veins and Deep Neural Network Sensors biometrics palm vein scanner multimodality convolutional neural networks |
| title | Contact-Free Multispectral Identity Verification System Using Palm Veins and Deep Neural Network |
| title_full | Contact-Free Multispectral Identity Verification System Using Palm Veins and Deep Neural Network |
| title_fullStr | Contact-Free Multispectral Identity Verification System Using Palm Veins and Deep Neural Network |
| title_full_unstemmed | Contact-Free Multispectral Identity Verification System Using Palm Veins and Deep Neural Network |
| title_short | Contact-Free Multispectral Identity Verification System Using Palm Veins and Deep Neural Network |
| title_sort | contact free multispectral identity verification system using palm veins and deep neural network |
| topic | biometrics palm vein scanner multimodality convolutional neural networks |
| url | https://www.mdpi.com/1424-8220/20/19/5695 |
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