Convolution Neural Network Based Covid -19 Face Mask Detection and Recognition

ABSTRACT

The coronavirus is devastating global health. Ac- cording to WHO guidelines, wearing a mask and keeping a 6-foot distance between people can help to prevent the spread of COVID 19. As a condition of the international COVID-19 outbreak, protective equipment, the most vital of which is a face mask, is required. Wearing a face mask in public is a good way to be safe. This project seeks to develop a real-time, GUI- based face detection and identification system using machine learning. Tensor Flow, Keras, Scikit-learn, and Open CV are used to develop a Convolutional Neural Network (CNN) model to make the technique as accurate as possible. Principal Component Analysis (PCA) and the HAAR Cascade Algorithm are two components of the proposed methodology. If the person in front of the camera is wearing a mask, the classification algorithm's result will be displayed by a green rectangle overlaid around the region of the face;otherwise, it will be represented by a red rectangle superimposed around the area of the face. © 2022 IEEE.