A Novel Detection Model and Analysis of Face Mask Detection by Using Machine Learning

Abstract

Since March 2020 Coronavirus (COVID-19) has affected the world very badly. As this Coronavirus decease spread mainly from person-to-person. Between people who are in close contact with one another through respiratory droplets produced when an infected person coughs, sneezes, or talks. These droplets can land in the mouths or noses of people who are nearby or possibly be inhaled into the lungs. Studies of this decease proved that wearing a face mask is one of the precautions to reduce the risk of viral infection of this decease. As it can help to prevent from viral transmission, at many public places as well as private places it is compulsory to wear a mask and correctly. Many public service providers are there where customers come to use that services. So, it is not possible to check manually whether customer has worn a mask or not. This technology can overcome this problem. In this paper we propose face mask detection using machine learning which is one of the efficient face mask detectors. The proposed system mainly consists of three steps that are. 1. Image pre-processing 2. Face detection and reading Dimensions 3. Face mask classifier. Our system is capable of detecting face with mask and without mask and it is integrated with webcam or cameras. This system will help to avoid the safety violation and will help to keep the track on safety.