[1]毛晓波,徐向阳,李楠,等.基于改进SSD和Jetson Nano的口罩佩戴检测门禁系统[J].郑州大学学报(工学版),2021,42(06):87-94.[doi:10.13705/j.issn.1671-6833.2021.06.002]
　Mao Xiaobo,Xu Xiangyang,Li Nan,et al.A Mask Wear Detection Access Control System Based on Improved SSD and Jetson Nano[J].Journal of Zhengzhou University (Engineering Science),2021,42(06):87-94.[doi:10.13705/j.issn.1671-6833.2021.06.002]

点击复制

基于改进SSD和Jetson Nano的口罩佩戴检测门禁系统()

分享到：

《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:

42

期数:

2021年06期

页码:

87-94

栏目:

出版日期:

2021-11-10

文章信息/Info

Title:

A Mask Wear Detection Access Control System Based on Improved SSD and Jetson Nano

作者:

毛晓波; 徐向阳; 李楠; 魏刘倩; 刘玉玺; 董梦超; 焦淼鑫

郑州大学电气工程学院;郑州大学机械与动力工程学院;

Author(s):

Mao Xiaobo; Xu Xiangyang; Li Nan; Wei Liuqian; Liu Yuxi; Dong Mengchao; Jiao Miaoxin;

School of Electrical Engineering, Zhengzhou University; School of Mechanical and Power Engineering, Zhengzhou University;

关键词:

口罩佩戴检测; 门禁系统; 目标检测SSD; Jetson Nano; MobileNet-V3

Keywords:

mask wear detection;  access control system;  object detection algorithm SSD;  Jetson Nano;  MobileNet-V3

DOI:

10.13705/j.issn.1671-6833.2021.06.002

文献标志码:

A

摘要:

为了减少疫情期间人们未佩戴口罩造成的交叉感染机会，设计了一款新颖的门禁系统，快速检测进出口行人是否佩戴口罩，以控制闸机的开合。采用改进的目标检测算法SSD，将原始的VGG特征提取网络替换为MobileNet-V3，取得了78%的MAP；将该模型移植到Jetson Nano开发板上，加装高清显示器，播放系统中的公益广告或者商业广告，并搭配可折叠的平行四边形档板，构成一个完整的多功能门禁系统。以MobileNet-V3为特征提取网络的SSD算法的检测速度为12FPS，与以VGG为特征提取网络的原始SSD算法相比，检测速度提高了6倍，具有良好的应用价值。

Abstract:

In order to reduce the chance of cross infection caused by people not wearing masks during the epidemic, a mask wearing detection access control system based on improved SSD and Jetson Nano is designed to quickly detect whether pedestrians at the entrance and exit wear masks and control the opening and closing of the gate. Firstly, 6 000 training pictures suitable for the system are extracted from the two data sets of MAFA and WIDER FACE, which are used as the training set and 2 000 as the test set; Secondly, the pixel level transformations such as random rue and saturation and geometric level transformations such as random expansion and random clipping are used to enhance the small targets in the data set, so as to add more samples to the data set and enhance the generalization ability of the detection network; Thirdly, the VGG feature extraction network of the original SSD is replaced by MobileNet-V3, which makes use of its speed advantage of depth-wise separable convolution, as well as the optimization strategies such as H-Swish activation function with less computation and lightweight attention mechanism (squeeze and excite) to accelerate the detection and improve the accuracy. Finally, the detection network is transplanted to Jetson Nano, an artificial intelligence edge computing device with limited computing power, equipped with high-definition display, design a foldable parallelogram baffle, and select appropriate peripheral equipment to form a multi-functional access control system with epidemic prevention value to quickly detect whether pedestrians at the entrance and exit of public places wear masks. The test results on the embedded device are as follows: the target detection algorithm SSD with MobileNet-V3 as the feature extraction network obtains 78% MAP and FPS is 12. Compared with the original SSD algorithm with VGG as the feature extraction network (FPS is 2), the detection speed is increased five times. Facts have proved that the system not only ensures the real-time performance, but also takes into account the detection accuracy, so achieves the balance of accuracy and speed.

常用功能