Face Mask Wearing Detection using Independent Component Analysis and Naïve Bayes Classifier

In this paper, a new method was developed to detect the face mask wearing conditions using both Independent Component Analysis as a feature extractor and naïve Bayes as a classifies. The method was tested using real face images. The dataset was used for both training and testing. The MATLAB is used as programming software. The achieved accuracy in the testing 92.67%. The method was also tested using real live face pictures. The results were excellent, and the accuracy was 87.29%.