Face Mask Wear Detection by using Facial Recognition System for Entrance Authorization

Abstract

Face Mask Wear Detection Device for Entrance Authorization is designed to ensure that everyone wears a face mask at all times in a confined space. It is one of the easiest methods to lower the rate of coronavirus infection and hence save lives. Asthma, high blood pressure, heart failure, and many other chronic conditions can be fatal to those who are infected by the novel Coronavirus (nCoV-21). Consequently, the goal of this research is for face mask wear detection devices that help to reduce the rate of Novel Coronavirus infection on-premises or in public places by ensuring that customers comply with Standard Handling Procedures (SOP) set by the Ministry of Malaysian Health (MOH). Customers' faces are recognized by this device whether or not they are covered by a face mask upon entry into a facility. Additionally, the use of this device can contribute to ensuring compliance with the maximum number of customers allowed on the premises. A facial recognition system is the goal of this study that uses technology designed as an individual disciplinary aid and follows the safety procedure at this critical time. This research was developed using the engineering design process development model which has four phases namely; identifying the problem, making possible solutions, prototype development and testing and evaluating the solution. Results indicate that the developed product can function effectively.Experts have discovered that using this product helps people stick to their face mask routines. The design of this product has improved, which means that the overall quality of the product is elevated to be capable of performing as intended in terms of intelligent technologies.

Face Mask Segmentation Method Combining Salient Features and Gender Constraints

“…Traditional face recognition technologies face many challenges in recognizing faces wearing masks, such as partial facial feature occlusion and light reflection caused by masks [6][7][8][9][10][11]. To address this issue, it is necessary to study a method that can effectively recognize and segment faces wearing masks [12][13][14][15][16][17][18][19][20]. By researching the face mask segmentation method that combines salient features and gender constraints, we can improve the face recognition accuracy under mask occlusion conditions, thus playing an important role in public safety, financial payment, access control systems, artificial intelligence monitoring, and health management.…”