Share Email Print
cover

Proceedings Paper • new

Uncovering vein pattern using generative adversarial network
Author(s): Gehua Ma; Biao Wang; Chaoying Tang
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Vein distribution is important in medical treatments. It could also be used for identity authentication1 . As a basic part of our body, the blood vessel has the merits of universality and distinctiveness. However, vein patterns are usually not visible in color images, which carries significant limitation. To address this limitation, we proposed a deep-learningbased method. Our method can uncover vein distributions from color images, help relieving pains to patients and widening the application scenarios of vein patterns. Experimental results showed that the proposed method has reliable performance and robustness in varying environments.

Paper Details

Date Published: 14 August 2019
PDF: 7 pages
Proc. SPIE 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019), 111793R (14 August 2019); doi: 10.1117/12.2539601
Show Author Affiliations
Gehua Ma, Nanjing Univ. of Aeronautics and Astronautics (China)
Biao Wang, Nanjing Univ. of Aeronautics and Astronautics (China)
Chaoying Tang, Nanjing Univ. of Aeronautics and Astronautics (China)


Published in SPIE Proceedings Vol. 11179:
Eleventh International Conference on Digital Image Processing (ICDIP 2019)
Jenq-Neng Hwang; Xudong Jiang, Editor(s)

© SPIE. Terms of Use
Back to Top