Multimodal student attendance management system (MSAMS)
Khaled Mohammed, Ahmed S. Tolba, Mohammed Mahfouz Elmogy · Ain Shams Engineering Journal · 2018
Effective student attendance management in higher educational institutions represents a big challenge for faculty members that need fast and accurate approaches. The traditional attendance manual approach is prone to spoofing and wasting a lot of faculty/students time and poor accuracy especially in the case of large student numbers. This paper presents an effective solution for the real-time student attendance management problem in large lecture halls. Fast response time and high accuracy imply using high-speed technologies and processes for student identification. In this paper, Radio Frequency Identification (RFID) and novel face recognition and identification approaches have been proposed and evaluated. A multimodal approach for student identification combined the power of both the traditional RFID approach and Multi-Scale Structural Similarity (MS-SSIM) index. Capturing the authentic face variability from a sequence of video frames has been considered for the recognition of faces and resulted in system robustness against the variability of facial features . Experimental results indicated an improvement in the performance of the proposed system compared to the state-of-the-art approaches at a rate between 2% and 5%. In addition, it decreased the time three times if compared with the state-of-the-art techniques, such as Extreme Learning Machine (ELM). Finally, it achieved an accuracy of 99%.