Implementation of Real-time Face Mask Detection with Convolutional Neural Network (CNN) and OpenCV

ABSTRACT

In this global pandemic of COVID-19, there is a critical need for self-protective devices, and the most important of them is a face mask. Our project’s main aim is for identifying the presence of a face mask on person's face. A strategy should be formulated to make the people accept this essential safety measure. To check this, a face mask detector system should be used. To check the presence of a face mask on a human face, the primary step is the detection of human face. This can be divided into two parts verifying faces on the images and detection of masks on their faces. Face masks are used to prevent cross-contamination as part of an infection control strategy. Using TensorFlow, Kera's library, and OpenCV, we created a very rudimentary convolutional neural network (CNN) model. Our experiment demonstrates that it operates effectively on test data, having a precision of 100% and a recall of 99%, respectively. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.