COVID-19 approved mask detection using mathematical morphology

Abstract

Face detection has multiple applications including recognition, people identification and detection of facial expressions. With the current pandemic crisis and due to the measures imposed to prevent Covid-19 spreading, the wearing of a protection mask became mandatory. The object of interest of this paper is to detect the wearing of an approved mask face using Viola Jones algorithm, aggregate channel features (ACF) and mathematical morphology. COVID-19 virus spread through the air, so it is necessary that all the materials used for manufacturing of the face masks to filter properly the air, and only the approved face masks to be used in order to control the spread infection. The algorithm used for face detection is Viola Jones with notable success in real time face detection and real time impression speed in face detection. Identification of the approved face mask against Covid-19 virus is made with a trained ACF detector. Eye detection, necessary to check if the face mask is properly placed, is based on mathematical morphology operators. These operations used together are robust with high results on the image processing.