ABSTRACT
Face recognition is one of the most widely used biometric identification systems due to its practicality and ease of use. The COVID-19 outbreak has recently expanded rapidly over the world, posing a major threat to people's health and economic well-being. Using masks in public places is an efficient approach to prevent the spread of infections. However, due to the absence of facial features detail, a masked face recognition system is a difficult task. We offer a technique to identify the masked faces in this project.Masked face recognition is a subset of occluded face recognition that requires prior knowledge of the obscured portion of the targeted face. Occluded face recognition is a current research topic that has captured the interest of the computer vision community. Occluded face recognition systems have previously been focused on detecting and recognizing an individual's face in the wild when the occluded part of the face is in a random form and position. Meanwhile, the nose, mouth, and cheeks of a masked face are frequently hidden. The eyes, brows, and forehead may be the only remaining clear areas. As a result, a masked face recognition system could effectively concentrate on analyzing traits that can be derived from the subject's uncovered portions, such as the eyes, brows, and forehead. © 2022 IEEE.