A Real-Time Web-based Facial Recognition Attendance System


  • Noradila Nordin Universiti Utara Malaysia
  • Yee Zhen Hong Universiti Utara Malaysia


Biometric, Facial recognition, Identification, Attendance management


Facial recognition has become an important part of biometric verification. A facial recognition system can detect, track, identify, and verify the identity of an individual based on their faces captured using a camera that can be still or in real-time images. Facial recognition can be used in the attendance management system to record the attendance of an individual in any sector, including education. In educational institutions, attendance marking is one of the methods used to monitor students’ presence in lectures. It is one of the ways to monitor their presence to ensure their participation in the lectures and class activities to enhance their academic achievement and reduce the frequency of absences without justifiable excuses. Typically, the conventional method used is through manual attendance marking on a piece of paper. This approach has been demonstrated to be forgery-prone, imprecise, and time-consuming as it is primarily dependent on the human factor. Thus, this paper proposes a web-based attendance system with facial recognition (WAS-FR). WAS-FR uses a live camera facial detection feed to display the student details and the current approximated location of the student in each of the student’s enrolled courses to avoid fake attendance. WAS-FR is based on the facial recognition model that compares the facial descriptors of the real-time image from the camera to an uploaded image kept in the database. The majority of the respondents who tested WAS-FR strongly agreed that the system is easy, effective, and convenient to be used, showing a high mean value of 0.93, giving the system positive results overall. The facial recognition attendance system can quickly complete the tasks of student attendance check-in, which improve the efficiency of lectures as the attendance is done individually by the students.




How to Cite

Nordin, N. ., & Hong, Y. Z. . (2022). A Real-Time Web-based Facial Recognition Attendance System. Multidisciplinary Applied Research and Innovation, 3(4), 153–160. Retrieved from https://publisher.uthm.edu.my/periodicals/index.php/mari/article/view/9712