Face Recognition Attendance System - Goel, Prachi; Ansari, Abdul Aleem; Jain, Apurva; Nagar, Anshul (International Journal of Computer Sciences and Engineering, 2023)
In today’s digital era, face recognition systems have emerged as a vital component across various sectors. As one of the most commonly used biometric technologies, face recognition offers a multitude of advantages including security, authentication, and identification. Despite its lower accuracy compared to iris recognition and fingerprint recognition, face recognition continues to gain traction due to its contactless and non-invasive nature. Moreover, it can be effectively utilized for attendance marking in educational institutions and workplaces, addressing the shortcomings of traditional manual methods such as consumption and the risk of proxy attendance. This paper proposes a class attendance system based on face recognition, aiming to streamline the attendance process and eliminate its associated challenges. The system encompasses four key phases: database creation, face detection, face recognition, and attendance updation. The database is created by capturing images of students in the classroom. Face detection and recognition are performed using the Haar-Cascade classifier and Local Binary Pattern Histogram algorithm, respectively. Faces are detected and recognized in real time using live streaming videos. At the end of each session, the attendance is automatically sent via email to the respective faculty.