Study and Analysis of Implementing a Smart Attendance Management System Based on Face Recognition Tecqnique using OpenCV and Machine Learning

Abstract

We can make our Attendance Management System (AMS) intelligent by using a face-to-face recognition strategy. For that, we have to fix a CCTV camera in the classroom at any best point, which makes a person's picture at a fixed time and tests a face-to-face image. Traditionally, student attendance at the institutes is manually reported on the attendance sheets. It's not a productive operation, because it takes 5 or more minutes for attendance. Normally, the length of our class is 50 minutes, and every day we have more than 5 lessons. So, both courses spend more than 50 minutes, which is almost the same as our class time. For, solving this big issue we are proposed a novel automatic technique namely "Face Detection with OpenCV". The system will be connected with our master database which includes the student's name, images, roll numbers, and time of attendance. This application mainly follows three steps. Firstly, it will take images. Secondly, compare them with the existing images which are storing in the master database. Thirdly, it will mark present all the matched images automatically on a spreadsheet and the remaining students will be absent from that class.