Finger Vein Recognition Based on Multi-Task Learning
Zhiang Hao, Peiyu Fang, Hanwen Yang · 2020
In finger vein recognition, traditional methods for extracting ROI based on edge detection, sliding window detection of joint lines, etc. need to set a fixed threshold, which contains many parameters that need to be adjusted. In the case of large illumination changes or poor image quality, the extracted results are not accurate enough. The existing feature extraction method also has a fixed operator pattern and limited extracted feature patterns. Therefore, a large amount of effective feature information is wasted.