Development of Face Recognition-Based Attendance System
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Date
2023-05
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Publisher
Faculty of Natural and Applied Sciences (FNAS) and the Faculty of Computing and Information Technology (FCIT), Sule Lamido University, Kafin Hausa, Jigawa State, Nigeria
Abstract
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.
Description
Keywords
Face Recognition, Class Attendance, OpenCV, Python