Face Recognition Technique based Student Attendance Management System

Teachers and administrators alike have a difficult time keeping track of student attendance. As a result, deep learning’s most recent developments are used to automate this process. This paper presents a facial recognition-based student attendance monitoring system built on Open CV (open-source computer vision library). It can detect objects like photos, educated face, or even just the writing of a person by processing photographs and videos. This system requires OpenCV, Pillow, and NumPy. The face characteristics of the students are detected and extracted from the collected photographs, which are then compared to the database and the attendance is recorded. A pattern recognition model will then be used to try to guess their identities, without human intervention, the process of keeping track of student attendance is maintained.