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Authentication is one of the significant issues in the era of the information system. Among other things, human face recognition (HFR) is one of the known techniques which can be used for user authentication. However, it is difficult to estimate the attendance precisely using each result of face recognition independently because the face detection rate is not sufficiently high. Continuous observation improves the performance for the estimation of the attendance we constructed the lecture attendance system based on face recognition and applied the system to the classroom. This paper first review the related works in the field of attendance management and face recognition. Then, it introduces our system structure and plan. Finally, experiments are implemented to provide evidence to support our plan. The result shows that continuous observation improved the performance for the estimation of the attendance.
As we are making a system which can recognize the face and match with its own database. It will make the attendance system more authentic. Our primary goal is to help the lecturers, improve and organize the process of track and manage student attendance and absenteeism. Additionally, we seek to provide a valuable attendance service for both teachers and students. Reduce manual process errors by providing automated and a reliable attendance system uses face recognition technology. Increase privacy and security which student cannot be presenting himself or his friend while they are not. Flexibility, Lectures capability of editing attendance records.
Our aim is to build up a face recognition system where a human will stand in front of the system and a camera will match the face along with its database. There will no extra RFID card people need to carry any more and this system will be the most authentic system of taking attendance. We will try to build this system as efficient as possible.
The system stores the faces that are detected and automatically marks attendance.
Ease of use is to manipulate and recognize the faces in real time using. Multiple face detection. Multipurpose software Can be used in different places.
Ease of use is to manipulate and recognize the faces in real time using. Multiple face detection. Multipurpose software Can be used in different places.