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


  • Imad Majed zeebaree Duhok Polytechnic Unversity
  • Omer Sedqi Kareem Duhok Polytechnic University




Face mask detection, Classification, Haar Cascades Classifier, Covid-19


The global epidemic causes extensive damage. Several sectors, including tourism and recreation, have been halted. Since these projects require work 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 metres away, in lighting conditions ranging from medium to normal, and with facial angles falling within a range of ±40°. Face accessories are allowed on targeted photos as long as they don't cover the face. In conclusion, this approach may reduce the cost of real-time identity verification labour.




How to Cite

zeebaree, I. M., & Kareem, O. S. (2023). Face Mask Detection Using Haar Cascades Classifier To Reduce The Risk Of Coved-19. International Journal of Mathematics, Statistics, and Computer Science, 2, 19–27. https://doi.org/10.59543/ijmscs.v2i.7845



Original Research Articles