AUTOMATIC STUDENT-BASED FACIAL RECOGNITION ATTENDANCE SYSTEM USING OPENCV
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Date
2022-02-10
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Faculty of Technology, Obafemi Awolowo University, Ile-ife, Nigeria
Abstract
For decades, attendance is taken in educational institutions to ensure that students are present in class, however it is mainly done manually. Manually taking attendance is a tiresome task, which is inconvenient for both the student and the lecturer while filling up the attendance sheet. As a result, the idea of building an automatic attendance system based on a unique biometric approach such as facial recognition to improve the accuracy of the attendance file was born. The goal of this research is to create an automatic student attendance system that can update an attendance file during a lecture in the shortest time feasible utilizing the students' facial attributes. The system was implemented in python environment using Opencv library and over 150 faces of 400level students of the department of Computer Science, University of Ilorin, Ilorin, were captured, registered, processed and lastly a report of the attendance was generated in a csv file. The result of this system shows that it was able to detect and recognize 150 student faces in under 15 minutes automatically and successfully recognized 94% of the students. With the successful implementation of the system, it is our believe that it will greatly reduce the time spent in taking attendance and can also be utilized at any educational institution.
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Salihu, S. A, Memudu, A. S, Akintola, A. G, Abikoye, O. C & Sadiku, P. O., (2022): Automatic Student-Based Facial Recognition Attendance System Using Opencv. An appraisal Proceedings of the OAU Faculty of Technology Conference, Obafemi Awolowo University, Ile-ife, Nigeria, (OAUTekConf 2022). 15-21