Gesture Recognition and Hand Tracking for Anti-Counterfeit Palmvein Recognition

被引:2
作者
Xu, Jiawei [1 ]
Leng, Lu [1 ]
Kim, Byung-Gyu [2 ]
机构
[1] Nanchang Hangkong Univ, Key Lab Jiangxi Prov Image Proc & Pattern Recognit, Nanchang 330063, Peoples R China
[2] Sookmyung Womens Univ, Dept AI Engn, Seoul 04310, South Korea
来源
APPLIED SCIENCES-BASEL | 2023年 / 13卷 / 21期
关键词
infrared environment; hand gesture recognition; hand tracking; palmvein recognition; PALMPRINT RECOGNITION;
D O I
10.3390/app132111795
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
At present, COVID-19 is posing a serious threat to global human health. The features of hand veins in infrared environments have many advantages, including non-contact acquisition, security, privacy, etc., which can remarkably reduce the risks of COVID-19. Therefore, this paper builds an interactive system, which can recognize hand gestures and track hands for palmvein recognition in infrared environments. The gesture contours are extracted and input into an improved convolutional neural network for gesture recognition. The hand is tracked based on key point detection. Because the hand gesture commands are randomly generated and the hand vein features are extracted from the infrared environment, the anti-counterfeiting performance is obviously improved. In addition, hand tracking is conducted after gesture recognition, which prevents the escape of the hand from the camera view range, so it ensures that the hand used for palmvein recognition is identical to the hand used during gesture recognition. The experimental results show that the proposed gesture recognition method performs satisfactorily on our dataset, and the hand tracking method has good robustness.
引用
收藏
页数:13
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