Face Recognition Attendance System

Abstract

One of the most effective image-processing applications is face recognition, which is essential in this technical world. For the purpose of verification, particularly in the context of student attendance, the recognition of human faces is an important concern. An attendance system using facial recognition is a step of identifying students by using face biometrics based on high-definition monitoring and other computer technologies. The implementation of this system aims to digitally transform the established method of recording attendance by calling names and keeping handwritten records. The methods used today to take attendance are difficult and time-consuming. Manual recording of attendance can be used to simply modify records which will lead to attendance proxy. This is the main reason for developing the facial recognition attendance system. The developed project uses Raspberry Pi as the main processing unit with the Raspberry Pi camera module. This developed project uses a cloud computing platform (Microsoft Azure) for face services and to retrieve data from the database. For the database of the student, SQLite was used in the developed project. The developed project was tested in terms of face detection, face recognition, and attendance marking. The developed project was able to detect, recognize and mark the attendance of the student with up to 90% accuracy.