Attendance Monitoring System using CNN

Abstract

Uniqueness or individuality of an individual is his/her face. Attendance check plays an important role in classroom management. Checking attendance by calling names or passing around a sign- in sheet is time-consuming, inefficient and especially the latter is open to easy fraud. The main aim of this project is to improvise the traditional systems and introduce a new approach using Deep Learning techniques that presents the detailed implementation of a real-time attendance monitoring system. We first capture an image of students in a classroom and utilize the OpenCV module to detect and frame the faces in that image. In the next stage we enhance these frames using an image enhancing model. In the final stage of the project, we build a Convolution Neural Network (CNN) to train these facial images and compare them with the student records that are stored in the database and hence update the attendance status of the students. Our system promises easy to maintain hassle free attendance system and with other integrations it can be used for other necessities of industries and is not limited to educational institutions.