International Journal of Nonlinear Analysis and Applications

Face mask detection methods and techniques: A review

Document Type : Research Paper

Authors

Department of Computer Science, College of Science, University of Baghdad, Baghdad, Iraq

Abstract

Corona virus sickness has become a big public health issue in 2019. Because of its contact-transparent characteristics, it is rapidly spreading. The use of a face mask is among the most efficient methods for preventing the transmission of the Covid-19 virus. Wearing the face mask alone can cut the chance of catching the virus by over 70\%. Consequently, World Health Organization (WHO) advised wearing masks in crowded places as precautionary measures. Because of the incorrect use of facial masks, illnesses have spread rapidly in some locations. To solve this challenge, we needed a reliable mask monitoring system. Numerous government entities are attempting to make wearing a face mask mandatory; this process can be facilitated by using face mask detection software based on AI and image processing techniques. For face detection, helmet detection, and mask detection, the approaches mentioned in the article utilize Machine learning, Deep learning, and many other approaches. It will be simple to distinguish between persons having masks and those who are not having masks using all of these ways. The effectiveness of mask detectors must be improved immediately. In this article, we will explain the techniques for face mask detection with a literature review and drawbacks for each technique.

Keywords

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International Journal of Nonlinear Analysis and Applications
Volume 13, Issue 1
March 2022
Pages 3811-3823
  • Receive Date: 10 November 2021
  • Revise Date: 03 December 2021
  • Accept Date: 02 February 2022