Abstract: The student attendance management system is designed to improve the traditional attendance system in educational institutions by implementing face detection and recognition using OpenCV. The objective of this project is to enhance the efficiency and effectiveness of the current attendance system. The existing system suffers from inaccuracies and inefficiencies, necessitating an upgrade.

Face recognition technology is employed in this system because it provides a unique and reliable means of identifying individuals. By utilizing Haar Cascade for face detection and the LBPH model for face recognition, the system maintains a database of cropped face images associated with corresponding labels. The LBPH algorithm is used to extract facial features, enabling individual student training. Ultimately, the system generates a spreadsheet that records the number of students present in the classroom, accompanied by live image or video capture.

By incorporating face recognition technology, this attendance management system aims to address the limitations of the traditional approach, offering improved accuracy and efficiency in recording attendance.

Keywords: LBPH, OpenCV, Haarcascade,Face recognition, Face detection,Spreadsheet.

PDF | DOI: 10.17148/IJARCCE.2023.125145

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