Automated Attendance System Using OpenCV

Student Attendance mainframe structure is defined to manage the student's class attending files using the concept of face detection and recognition through open computer vision. The principle reason this system has been put forward is to improve the traditional attendance system of various universities to avoid the misuse of time and assets. The pointing-sides of automation world have forced an idea of switching from standard attendance to the digital system by using face detection and recognition methods. This is how the Student Attendance structure is being developed by introducing the dataset of an individual. The major reason of building this system is to improve the adaptability and performance of the attendance system procedure besides reducing the long term time load, work and disposables used. The main purpose of the Student Attendance markup structure is to perform, adding and manipulating attendance notes of an individual, automatic calculation on number of presentees and absentees based on subject and affability of the class and then generates the automated document or spreadsheet. This idea is completely based on general purpose language named as python through which we use the concept of open computer vision. For face detection system we used haarcascade and for face recognition, we used LBPH model; then the training of individual student happened and finally the system generates the spreadsheet which provides the no. of students present in classroom with an image or video capturing live.