• Keshav Rasal
• Rohit Patil
• H. R. Kulkarni
• Vishal Waghole

Traditional attendance management systems in educational institutions are inefficient, error-prone, and susceptible to proxy attendance. This research presents an automated attendance system leveraging facial recognition technology to overcome these limitations. The proposed system integrates computer vision and machine learning techniques using OpenCV, dlib, and the face_recognition library, along with SQLite for database management, to deliver a real-time, contactless attendance solution. The system’s modular architecture includes enrollment, encoding, and recognition modules, ensuring scalability, accuracy, and maintainability. Experimental results indicate significant improvements in accuracy (92–97%), efficiency, and security compared to manual and RFID-based systems. The solution eliminates fraudulent attendance, reduces administrative workload, and provides hygienic, non-contact operation. Findings demonstrate the system’s technical feasibility and practical applicability for institutional and organizational environments.

Face Recognition, Automated Attendance, Computer Vision, Machine Learning, OpenCV, Biometric Authentication

"Automated Attendance System Using Face Recognition: A Computer Vision Approach to Institutional Attendance Management", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.13, Issue 1, page no.539-546, January-2026, Available :http://www.jetir.org/papers/JETIRHG06067.pdf

"Automated Attendance System Using Face Recognition: A Computer Vision Approach to Institutional Attendance Management", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.13, Issue 1, page no. pp539-546, January-2026, Available at : http://www.jetir.org/papers/JETIRHG06067.pdf