Development of Face Recognition-Based Attendance System

Okechukwu. M. Chukwude, Nazmat. T. Surajudeen-Bakinde, Sikiru .O. Zakariyya, Joy. B. Ogunsakin,Jimoh. Akanni, Sunday. A. Olayanju, Frederick. O. Ehiagwina

Keywords: Face Recognition, Class Attendance, OpenCV, Python

Lecture attendance management is usually tedious, and time-consuming and may be prone to errors or manipulations when done manually. Hence, in this work, a web application called RollCall was developed and tested, for use by both students and lecturers in the Faculty of Engineering at the University of Ilorin as a model to manage attendance. The system manages attendance by allowing the lecturers to create courses, and take and retrieve attendance records for the courses created. Student functionalities include uploading their face data, enrolling for courses, and retrieving attendance records for the courses in which they enrolled. Attendance is marked through face recognition technology implemented with Python, OpenCV and Sci-kit Learn. The web interface was implemented using HTML5, Twitter Bootstrap CSS framework and JavaScript. The findings revealed that RollCall effectively streamlined attendance management, making it easier for both students and lecturers to keep track of attendance records. The web application is user-friendly and enhances the overall academic experience by improving the accuracy and efficiency of attendance management.