Please use this identifier to cite or link to this item:
http://210.212.227.212:8080/xmlui/handle/123456789/306| Title: | FINGER VEIN BIOMETRIC RECOGNITION USING CONVOLUTIONAL NEURAL NETWORK |
| Authors: | Gayathri, Chandralal Natheera, Beevi M |
| Issue Date: | May-2022 |
| Series/Report no.: | ;TKM19MCA011 |
| Abstract: | The use of human finger-vein traits for the purpose of automatic user recognition has gained a lot of attention in recent years. Current state-of-the-art techniques can provide relatively good performance, yet they are strongly dependent upon the quality of the analysed finger-vein images. In this paper, I propose a convolutional-neural-network-based finger- vein identification system and investigate the capabilities of the designed network over four publicly available databases. The main purpose of this paper is to propose a deep-learning method for finger-vein identification, which is able to achieve stable and highly accurate performance when dealing with finger-vein images of different quality. The reported extensive set of experiments show that the accuracy achievable with the proposed approach can go beyond 95 percent correct identification rate for all the four considered publicly available databases. Index Terms :- Convolutional neural network, finger-vein, biometrics, identification. |
| URI: | http://210.212.227.212:8080/xmlui/handle/123456789/306 |
| Appears in Collections: | 2022 |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| M19MCA11_S6_Finger Vein Biometric Recognition using CNN - GAYATHRI CHANDRALAL 1028.pdf | 1.27 MB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.