CAD System Based on Face Mask Recognition for Respiratory Infections Diseases Hospital

Abstract

The infection of respiratory diseases can be eliminating and controlling by wearing face mask in contaminated areas. However, to control people about wearing face mask it has been challenging unless the automatic recognitions are applied. Therefore, in this paper, a Face Mask Recognition System by Computer Aided Design (CAD) is introduced. The proposed design system is based on face, mouth and nose detections in captured image. The CAD system considers to be implemented for specialized respiratory diseases hospital with different departments, each department controlled by separated door. The main goal of this paper is to design system based on software programs that helps reduce the spread of respiratory diseases and controlling wearing face mask inside respiratory infection diseases hospital based on mask detection and mask color detection. The proposed system designed for hospital with three respiratory diseases departments and three mask color applied each mask color for each department. The mask recognition system has been used cascaded object detector that is Local Binary Pattern Histogram LBPH algorithm, then color detection as artificial intelligence-based method, Red, Green, and Blue (RGB) color of the face mask images. Finally, by using of Convolutional Neural Network (CNN), the classification accuracy of color recognition achieved 100%, and also the whole system functionality tested successfully obtained all results by testing accuracy 95%. The hardware designing circuit simulation in Proteus software were obtained to control the systems of hospital department doors based on the results obtained from MATLAB software.