An Integrated Face Recognition based Attendance Monitoring System

Everything in the world today is mechanised and connected online. Where everything can be done by machine automatically. Such as it is difficult to deal with the presence of several students in a classroom under the conventional approach. As it is time consuming and there are chances of human errors taking attendance. Marking attendance is a day-to-day activity which is a real-world problem which can be solved using Face recognition. It is also efficient handling bulk of student's attendance than old traditional methods. Attendance systems come in a variety of forms, such as biometric, facial recognition, radio frequency card, and conventional paper-based ones. A facial identification-based attendance system is the safest and most efficient of them all. This paper presents an integrated system which automatically detects face and marks the attendance in the sheet. While building this system, we basically focused on two Machine Learning algorithms that are Haar Cascade and Local Binary pattern Histogram Algorithm (LBPH) also we used Python and OpenCV libraries which is used to make the model more efficient.