Which finger is the best for finger vein recognition?
| Autor: | He Zheng, Liao Ni, Wenxin Li, Yapeng Ye, Shilei Liu |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
0301 basic medicine
Biometrics business.industry Computer science Index (typography) Word error rate 02 engineering and technology Thumb Finger vein recognition body regions 03 medical and health sciences Identification (information) 030104 developmental biology medicine.anatomical_structure 0202 electrical engineering electronic engineering information engineering medicine 020201 artificial intelligence & image processing Algorithm design Artificial intelligence Set (psychology) business |
| Zdroj: | BTAS |
| Popis: | Finger vein recognition is a biometric method utilizing the vein patterns inside one's fingers for personal identification. Every user has 10 fingers in total, among which the index fingers and middle fingers from left and right hands are the most common used fingers in finger vein recognition systems, for their suitable length, width and flexibility. No evidence shows any significant relationship between one's different fingers, so they are usually treated as different classes in recognition. However, what is the difference between different fingers? How do they perform in finger vein recognition systems? Some researchers believe that index fingers perform better than middle fingers, while the others hold contrary opinions. There is not a consensus on this topic. In this paper, we conduct a set of experiments on different fingers, with different recognition algorithms and different databases. The result shows that considering the equal error rate and DET curve, the performance of different fingers is quite different in different algorithms and database. Therefore the performance of fingers is algorithm and database dependent. Based on the finding, we propose a method to improve the performance of finger vein recognition systems. The rationale of our method is that we assume every user has a “best” finger in certain scenarios, and the “best” finger for each user may be different. Then we design an algorithm to find their best fingers and suggest them to use it. Evaluation results show that if the users use their “best” fingers as our method suggests, the EER of the system decreases up to 60%. This means the proposed method can improve the performance of finger vein recognition system at a significant level without any change on the algorithm. |
| Databáze: | OpenAIRE |
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