Year: 2025
Type: article
Abstract: : Current attendance systems often face issues like proxy attendance, time consumption, and data manipulation, leading to inaccuracies and inefficiencies. "Facial Attendance Management System Using Python" provides an in-depth analysis of the facial attendance management system, which offers the best statistics and accuracy in identifying individuals, enhancing efficiency, and ensuring secure and reliable attendance tracking. It is an automated solution that utilizes Python and its libraries for marking real-time attendance using facial recognition technology. This approach replaces traditional attendance methods, minimizing human intervention and reducing errors such as proxy, time consumption, and data manipulation. The implementation contains OpenCV for image processing, NumPy, Pandas for efficient data handlimg & Matplotlib for statistical representation. The system captures facial images of the students, train them, and matches with the database records using Machine learning. It integrates with MySQL to securely store the images and manage the attendance records. The performance of the proposed model has been compared with several other modelsand the proposed model has shown significant improvement in terms of accuracy over other model. Keywords -- Python and it’s library, OpenCV, Facial Recognition , Automation, Attendance System, Machine Learning.
DOI: 10.55041/ijsrem47282
Author: Khushi Maddheshiya
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4410191612