Face Recognition Attendance System Using Local Binary Pattern Algorithm

Abstract

In the digital age of today, face recognition technology is essential and is utilized by almost all businesses. one of the technologies that made the most use of biometrics. It can be used for authentication, identification, and security and offers numerous benefits. Despite the fact that the method is non-invasive and contactless, it is still frequently used because it is less accurate than iris and unique mark ID. Organizations, universities, and other educational establishments can also make use of the facial recognition technology to monitor students' attendance. The current manual method is cumbersome and difficult to maintain, so this system aims to create a facial recognition-based system for tracking class attendance. Proxy attendance may also be an option. As a result, demand for this system has increased. Database creation, face detection, face recognition, and attendance update are the four stages of this system. Databases are created with images of students in class. For face recognition and detection, the Haar- Cascade classifier and the local binary pattern histogram method are utilized, respectively. Faces are perceived and distinguished in the homeroom's live-transferred video. Attendance records will be mailed to the relevant lecturers at the conclusion of the session.