Student Attendance Monitoring System Using Face Recognition

Abstract

There is no reason that a critical educational practise like attendance should be viewed in the old, tedious manner in this age of rapidly evolving new technologies. In the conventional method, it is difficult to manage large groups of students in a classroom. Since it takes time and has a high risk of error when entering data into a system, it is not recommended. Real-Time Face Recognition is a practical method for dealing with a large number of students' attendance on a daily basis. Many algorithms and techniques have been developed to improve face recognition performance, but our proposed model employs the Haarcascade classifier to determine the to determine the positive and negative characteristics of the face, as well as the LBPH (Local binary pattern histogram) algorithm for face recognition, all of which are implemented in Python and the OpenCV library. For user interface purposes, we use the tkinter GUI interface.