The Facial Recognition-Based Attendance System By Using OpenCV.

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.

Authors

Publication Details

Journal
Journal of engineering sciences.
Published
2025-01-01
DOI
https://doi.org/10.36893/jes.2025.v16i04.027
Primary Topic
IoT-based Smart Home Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

The Facial Recognition-Based Attendance System By Using OpenCV.

S. Nafisa Afreen, SMT.N.GANGADEVI
Journal of engineering sciences.
IoT-based Smart Home Systems
article

The Facial Recognition-Based Attendance System By Using OpenCV.

S. Nafisa Afreen, SMT.N.GANGADEVI
article en

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.

Journal of engineering sciences.Vol. 16(04)
Openalex Percentile: Top 95%
IoT-based Smart Home Systems
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