International Conference on Computer and Knowledge Engineering

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Facial Mask Wearing Condition Detection Using SSD MobileNetV2

Authors :

Amirhossein Tighkhorshid¹ Yasamin Borhani² Javad Khoramdel³ Esmaeil Najafi⁴

1- K. N. Toosi university of technology 2- K. N. Toosi University of Technology, Tehran, Iran 3- Tarbiat Modares University 4- K. N. Toosi University of Technology, Tehran, Iran

Keywords :

Facial mask detection،Facemask wearing classification،Covid-19،SSD MobileNetV2،Deep Neural Networks

Abstract :

Wearing a facemask is one of the main ways to prevent the spread of respiratory diseases such as Covid-19, so it is helpful to monitor people's facemask-wearing status through vision-based systems. In this paper, a system has been developed that divides the people's face mask-wearing conditions using image processing into three classes: without a mask, correct mask-wearing, and incorrect mask-wearing. For this purpose, the SSD-MobileNetV2 neural network has been used, and several hyperparameter sets have been compared for the best possible accuracy. Also, a lightweight custom CNN has been used as the second stage to improve the classification accuracy, so this stage can be used in cases where higher accuracy is required. Finally, the proposed neural network was implemented on a Raspberry-Pi3, and this system can control an entrance gate using a servo motor automatically.