| Autor: |
Sungchul Cho, Beom-Seok Oh, Donghyun Kim, Kar-Ann Toh |
| Jazyk: |
angličtina |
| Rok vydání: |
2021 |
| Předmět: |
|
| Zdroj: |
IEEE Access, Vol 9, Pp 86914-86927 (2021) |
| Druh dokumentu: |
article |
| ISSN: |
2169-3536 |
| DOI: |
10.1109/ACCESS.2021.3089484 |
| Popis: |
In this paper, we investigate into utilization of images from the visible light (RGB) spectrum for identity verification based on the palm-veins. This is differentiated from the commonly utilized Near-infrared (NIR) images for palm-vein feature extraction. Our goal is to explore into the often omitted palm-vein information from the RGB palm images considering the vast deployment of the RGB cameras. Essentially, the vein line features are extracted at various scales based on an efficient difference image projection. The extracted features from the gallery and the probe images are matched based on a fast Hamming distance implementation. The resultant similarity scores are finally fused at score level for accuracy enhancement. Experiments are conducted on two public multi-spectral palm databases. The results show encouraging matching accuracy and computational efficiency of the proposed method which extracts the palm-vein utilizing only the visible spectrum. The outcome of this study can be deployed as a standalone biometric or as part of a multibiometric system for secure authentication. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
|
