Face Mask Detection Using Haar Cascades Classifier To Reduce The Risk Of Coved-19

Abstract

The global epidemic causes extensive damage. Several sectors, including tourism and recreation, have been halted. Since these projects require working together in close contact, it increases the danger of infection. To reduce the spread of COVID-19, keep a safe distance from others and always wear protective clothing. In light of this, we have developed COVID Vision, a system that uses Haar cascades as a classifier for a face mask detector. This will reduce reliance on employees while maintaining COVID-19 criteria. COVID Vision can determine if someone is wearing a mask or covering their lips live. According to the findings, the suggested system correctly displays the output result of human face detection within a range of 0.6 to 1.35 meters away, in lighting conditions ranging from medium to normal, and with facial angles falling within a range of ±40°. If they don't cover the face, face accessories are allowed on targeted photos. In conclusion, this approach may reduce the cost of real-time identity verification labor.