Face Mask Detection Using Convolutional Neural Network

ABSTRACT

COVID-19 is one of the most dangerous forms of diseases which is caused by corona virus. It is a highly transmissible disease. WHO has already declared it as a pandemic.Therefore at the current scenario, due to outbreak of this pandemic (COVID-19), face masks has become the necessary tool of everyone to avoid spread of disease to some extent. There has been a great demand for the development of software which can easily recognize person who is wearing a mask. Therefore we are going to develop a system which will fulfill the need using Deep Learning. We will use convolutional neural network to train our model. Here two categories of dataset will be used. The one which contains set of images of faces with mask and the other without face masks We will train the program with this data set to learn to decide whether a person's face is masked or not. OpenCV, tensorflow and keras will be used for the real time face detection with live stream through web camera. After the successful deployment of the product, we will be able to design a software which can be installed at various places such as at the entry gate of colleges, railway stations , air ports , temples, hotels and shops etc. This will easily detect the persons who are entering without face masks by using cameras of the systems. Hence this product is the need of the hour for us to develop so as to work for the safety of humans. © 2021 IEEE.