Face is an important part of a person, it is used to identify and differentiate identities of two or more individuals in real world. Different parts of the body have been exploited over the recent years, to ensure that only the legitimate individual has access to their respective accounts both in real world and in virtual. Different methods have been created, one being Biometrics, which consists identifiers such as Fingerprint, Palm veins, DNA, Palm print and Face recognition etc. Similarly, this project seeks to use one distinctive identifier of Biometrics, Face Recognition.
The project has created a working Automated Facial Recognition System for Coventry University and its students. With the use Open CV library through programming language, Microsoft Visual Studio C#, OpenCV consists of Voila and Jones machine learning algorithms for face detection and extraction, which is stored in built T-SQL Database built inside Microsoft Visual Studio. Object classifier called Eigen Object Detector, is used to match the faces detected with camera against the one stored in the SQL Database. The system is programmed fully with Microsoft Visual Studio 2017.
The motivation behind this project was to help Coventry Students, to make it easier for them to record their attendance by not having to be dependent with Card-systems, as Student cards are often lost and paid to replace. This means they cannot prove their identity and record attendance instantly. The card-system is also at fault often with inaccurate attendance recordings, as it can be tricked or fooled, when individuals are able to record attendance for others. In the event when card system is offline, paper-based system have to be used in this event. This makes more time consuming for students and makes it harder for them to focus on the lecture/lab sessions.
The project’s main objective was to find out if the Facial recognition system is effective at recording attendance of Coventry University students than Card-based system/paper-based system that is currently in place. By implementing and testing, The Automated Facial Recognition Attendance System and reviewing the system with the students of Coventry University, it is concluded that it more effective at recording attendance, as most factor being that it saves, the students of Coventry University, valuable time and makes it easier for them to record their attendance.