Real-Time Face Mask Detector Using YOLOv3 Algorithm and Haar Cascade Classifier
Truong Quang Vinh, Nguyen Tran Anh
Abstract
During the pandemic of Covid-19, wearing face mask in some factories, departments, or working offices is required. This paper presents a real-time face mask detector which can alarm when detecting a person without wearing a face mask. Moreover, the system can recognize the person who wears a face mask incorrectly, or wear other things except a face mask. The proposed algorithm for face mask detection in this system utilizes Haar cascade classifier to detect the face and YOLOv3 algorithm to detect the mask. The whole system has been built and demonstrated in a practical application for checking people wearing face mask at the office entrance. The experiment result shows that the accuracy of the system can achieve up to 90.1%.