Abstract
In this paper, a face detection-based attendance system is proposed and the comparison between different algorithms is evaluated. Haar cascade is used for face detection and for face recognition is implemented through LBPH, fisher face and eigenface. Real-time images are captured by using a camera and stored in the dataset. During prediction, the person’s image is recognized and the database is updated with that person’s id and the changes will get reflected in the excel sheet as well. The SMS is also sent to an appropriate number given by the student. The comparison is done among the three methods, and the best one is chosen. This paper also tells about preferring of OpenCV over MATLAB.
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Meena, K., Swaminathan, J.N., Rajendiran, T., Sureshkumar, S., Mohamed Imtiaz, N. (2022). An Automated Attendance System Through Multiple Face Detection and Recognition Methods. In: Raj, J.S., Kamel, K., Lafata, P. (eds) Innovative Data Communication Technologies and Application. Lecture Notes on Data Engineering and Communications Technologies, vol 96. Springer, Singapore. https://doi.org/10.1007/978-981-16-7167-8_17
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