Year: 2025
Type: article
Abstract: Traditional attendance systems, such as manual sign-ins or RFID-based methods, are time- consuming, prone to errors, and susceptible to manipulation. This paper presents a Smart Attendance System that leverages facial recognition technology to automate attendance tracking. The system integrates advanced face detection and recognition algorithms, along with anti-spoofing mechanisms, to ensure secure and efficient attendance marking. The proposed system uses the OpenCV library for face detection, the FaceNet algorithm for facial recognition, and Fourier Spectrum Analysis for anti-spoofing. Built with Python and Tkinter, the system provides a user-friendly interface for real-time attendance logging and management. The results demonstrate high accuracy in face recognition, efficient processing, and robust security against spoofing attempts, making it a reliable solution for modern attendance management in educational and corporate environments.
Authors: A. J. Patil, Girija Beldar, Bhagyashri Gadekar, Rajanee Gund, Shital Gund, Priyanka Khyade
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W3148940967