Detection of a Facemask Using Convolution Neural Network

Abstract

Due to the COVID-19 pandemic, wearing the mask has become obligatory in public locations as it gives a most preventive impact in opposition to viral transmission. It has affected our day-to-day life to a greater extent. Though people had got vaccinated, mask wearing, social distance maintenance and sanitization need to be practiced probably till the pandemic gets vanished. Proposed work layout a real-time deep learning version to satisfy current demand for detection of facemask wearing position of someone earlier than he or she enters a public place. This paper provides a simplified method for achieving the intended goal in machine learning applications such as TensorFlow, Keras, OpenCV, and MobileNet. The proposed approach determines how the face mask is worn in real time; it leverages live image captures that provide accurate information about whether a person is wearing the mask appropriately. The parameters of the convolution neural network model are used to detect the presence of facial mask(s). The proposed approach attains the accuracy that is almost nearer to 99.75%.