Real-Time Face Detection Attendance Management System - Min, Hau Wen; Ab Ghafar, Aimi Syamimi (Journal of Advanced Industrial Technology and Application, 2022)
The issue of human error, inaccurate and time-consuming of manual attendance system gradually magnified the inefficiency and obsolescence of the system. An automatic attendance management system with face detection will increase the efficiency, accuracy, and security of a system in attendance taking task. Real-Time Face Detection Attendance Management System is concerned in finding human faces through real-time with the attendance taken and saved as reference for future. Face detection system is implemented by using Haar Cascades Classifiers for the object detection. Attendance system is managed with a database management system called MySQL using SQL programming language. Real-Time Face Detection Attendance Management System able to detect front face and manage the attendance in real-time. A text box will display for the attendee to enter their name for the purpose of attendance taken when face is detected. The attendance list and image collection in the database will auto increment and update in MySQL. The accuracy of Real-Time Face Detection Attendance Management System is shown with the comparison between different front face condition in different illumination condition. The result is tested with 4 sets of the attendee’s face in different illumination and different front face condition. 94.44% accuracy of the face detection system is shown from the result taken by the system. The image acquisition for every attendee is collected and saved in the right folder. The attendance is taken with the attendee’s name, date and time in attendance database and image is save into face database. Some technology such as anti-spoofing measures, mask detection and deep learning concept are recommended to be added into the system for future improvement