Shirish Mohan Dubey, Anubhav Anand, Bhavya Agrawal, Garvit Mathur | International Journal of Digital Communication and Analog Signals | Vol 10, Issue 01 | pp. 1-6 | ISSN: 2455-0329
Abstract
The goal of this project is to develop a facial recognition-based attendance system for educational institutions to improve and modernize the current system and make it more effective and efficient than it was in the past. The distinctive features of the human face allow for individual identification. Since there is little chance of a face deviating or being duplicated, it is utilized to trace identification.The article also covers the advantages of putting automated attendance systems in place, such as increased security, convenience, accuracy, and efficiency. It showcases case studies and real-world implementations from a range of industries, highlighting the usefulness and success stories of implementing face recognition-based attendance systems. To provide dependable and durable attendance tracking systems, it looks at how cameras, image processing techniques, machine learning models, and database management systems can be integrated. PCA, SVM, viola jones, OCR are the algorithms that are used. Once the student's face was identified, the attendance was updated on an Excel page.
Face recognition, face detection, OCR, PCA, SVM, viola jones
Keywords
SVM, PCA, Face recognition, OCR, face detection
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How to cite this article
@article{DubeySM2024,
author = {Shirish Mohan Dubey and Anubhav Anand and Bhavya Agrawal and Garvit Mathur},
title = {Facial Recognition in Education: Revolutionizing Attendance Tracking for Enhanced Efficiency and Security},
journal = {International Journal of Digital Communication and Analog Signals},
year = {2024},
volume = {10},
number = {01},
pages = {1--6},
issn = {2455-0329},
url = {https://journalspub.com/publication/uncategorized/article=9099}
}