Detection of Face Mask During Pandemic of Covid-19

ABSTRACT

The global pandemic caused due to COVID-19 has badly affected the entire world in all the different sectors. With the increasing number of cases of coronavirus, it becomes very necessary for the people to wear a mask, maintain social distancing, and maintain proper sanitization of themselves as well as their surroundings. However, some people are not serious about wearing a mask. Thus, it is necessary to develop a system that can detect the people violating this rule of not wearing a mask. Our system gives provision to detect the people who have not worn the mask appropriately or have not at all worn the mask. Face detection is one of the major problems, to overcome this problem various algorithms are being developed using different architectures. The convolutional architecture has made it possible. Our motive is to design a binary classifier that can detect any face in front of the frame and produce accurate output. Our model has shown very good results in detecting the faces without a mask as well as it is also able to detect the multiple facial mask images in a single frame. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.