Face Mask Detection using Open-Source Computer Vision Library and Scikit-Learn using Machine Learning

Abstract

In this pandemic has rapidly affected our day to-day life disrupting the world trade and movements. Wearing a protective face mask has become anormal. In the near future, many public service providers will ask the customers to wear masks correctly to avail of their services. Therefore, face mask detection has become a crucial task to help global security. This project presents a simplified approach to achieve this purpose using some basic Machine Learning packages like OpenCV and Scikit-Learn. The proposed method detects the face from the image correctly and then identifies it has a mask on it or not. As a surveillance task performer, it can also detect a face along with the mask in motion. This method attains accuracy almost up to 90% on two data sets. We explore optimized values of parameters using the Viola Jones detection framework used to detect the presence of masks correctly without causing over-fitting.