| 한글제목(Korean Title) |
생체 인식 인식 시스템을 위한 주의 인식 잔차 분할 |
| 영문제목(English Title) |
Attention Aware Residual U-Net for Biometrics Segmentation |
| 저자(Author) |
앤디
이효종
Aung Si Min Htet
Hyo Jong Lee
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| 원문수록처(Citation) |
VOL 29 NO. 02 PP. 0300 ~ 0302 (2022. 11) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
Palm vein identification has attracted attention due to its distinct characteristics and excellent recognition accuracy. However, many contactless palm vein identification systems suffer from the issue of having low-quality palm images, resulting in degradation of recognition accuracy. This paper proposes the use of U-Net architecture to correctly segment the vascular blood vessel from palm images. Attention gate mechanism and residual block are also utilized to effectively learn the crucial features of a specific segmentation task. The experiments were conducted on CASIA dataset. Hessian-based Jerman filtering method is applied to label the palm vein patterns from the original images, then the network is trained to segment the palm vein features from the background noise. The proposed method has obtained 96.24 IoU coefficient and 98.09 dice coefficient. |
| 키워드(Keyword) |
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| 파일첨부 |
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