Year: 2025
Type: article
Abstract: Traditional attendance tracking methods in educational institutions and organizations often rely on manual processes, which are time-consuming and prone to errors and fraudulent practices such as proxy attendance. To address these challenges, this paper presents an automated attendance system leveraging facial recognition technology implemented using OpenCV. The system captures real-time images, detects and recognizes faces, and records attendance by matching the detected faces against a pre-registered database. Utilizing Python and OpenCV, the system ensures efficient face detection and recognition, enhancing accuracy and reducing processing time. This approach streamlines the attendance process and improves security by minimizing the potential for proxy attendance. The proposed system demonstrates high accuracy under various lighting conditions and poses, making it a robust solution for real-world applications.
Source: Journal of engineering sciences.
Authors: SYED AFREEN, SMT.N.GANGADEVI
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4409238305