Face Mask Detection Using Image Processing and Convolutional Neural Networks

Face masks have become a crucial part of our everyday lives as the number of COVID cases around the world has increased, and new varieties appear every few months. We must wear a mask every time we walk outside, so the installation of face mask detectors in public places has become quite significant. In this study, we use image processing to create a face mask detection system on cascading multiple architectures of convolutional neural networks (CNN) and deep neural networks (DNN), with investigate the findings using MobileNetV2, Xception and ResNet152V2 models. The proposed technique was able to obtain excellent accuracy by training the system with CNN and DNN architectures.