Automatic Class Attendance System Using Biometric Facial Recognition Technique Based on Raspberry Pi
A. A. Shabaneh, S. Qaddomi, M. Hamdan, A. Abu Sneineh, T. Punithavathi
V56 - N3 / 2023 Ordinario
Face recognition, raspberry pi, authentication, automatic, database, openCV
This study presents a novel automatic class attendance system that uses a biometric facial recognition technique based on Raspberry Pi and a camera module. Furthermore, the operation of the detection algorithm is accomplished by calculating the distance between the eyes; distance from the forehead to the chin; distance between the nose and mouth; depth of the eye sockets; shape of the cheekbones; and contour of the lips, ears, and chin. The developed face recognition system works with four major steps: capturing and scanning, extracting, comparing, and matching the captured image. The developed system recognizes students' faces in real time to handle the daily task of tracking students' attendance instead of using a manual method. The Raspberry Pi 3 model B+ microprocessor combined with the open-source libraries of Python, such as OpenCV, and a camera module are implemented in the facial biometric identification and recognition algorithm for recording attendance. The performance of the developed recognition system exhibits a high accuracy of 100% with a fast detection time of 1 s. In addition, the developed system has the ability to capture a student's face at a distance of 1.25 cm from the camera and alongside student's face orientations of 0° and 45°. The developed system performs fast and authentically, and thus, it is worthy of integration into any application.