Real Time Attendance Monitoring System using Face Recognition

The management of the attendance can a huge burden on the teachers if it's done by hand. To solve this problem, a smart and auto attendance management system is being used. However, authentication is a significant issue in this system. The smart attendance system is commonly executed with the assistance of biometrics. Facial recognition is one of biometric methods to enhance this system. By using this framework, the situation of proxies and students being marked present despite their physical absence can easily be resolved. The main implementation steps used in these types of systems are facial detections and recognizing the detected faces. This paper suggests a model for implement an automated attendance management system for students of a class. The suggesting system makes the usage of Haar classifiers, OpenCV and LBPH algorithm. Following facial recognition, attendance reports will be produced and store in excel formats. The system is experimented under various conditions like illumination, head moves, the changes of distance between the student and cameras. After intensive testing, overall complexities and accuracies are calculated. The Suggested system demonstrated to be an effective and powerful device for taking attending in a classroom without any time use and manual works. Keywords – Face Recognition, Face Detection, OpenCV, Haar Classifiers.