Class-based Digital Attendance Management System with Computer Vision

Attendance taking is an age long practice used to validate a student’s presence in class. The traditional attendance system is done with pen and paper where students write their names on the attendance sheet. This method is marred with a lot of irregularities, inefficiencies and proxy attendance(s)...

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Main Authors: Ngonadi, Ifeoma V., Ajiroghene, Sunday
Format: Article
Language:English
English
Published: INTI International University 2022
Subjects:
Online Access:http://eprints.intimal.edu.my/1663/
http://eprints.intimal.edu.my/1663/1/ij2022_27r.pdf
http://eprints.intimal.edu.my/1663/2/165
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author Ngonadi, Ifeoma V.
Ajiroghene, Sunday
author_facet Ngonadi, Ifeoma V.
Ajiroghene, Sunday
author_sort Ngonadi, Ifeoma V.
building INTI Institutional Repository
collection Online Access
description Attendance taking is an age long practice used to validate a student’s presence in class. The traditional attendance system is done with pen and paper where students write their names on the attendance sheet. This method is marred with a lot of irregularities, inefficiencies and proxy attendance(s) where students record attendance for their friends and classmates who are not present in class. This paper, therefore, develops an attendance management system that leverages on computer vision technology to detect and recognize faces and a file management system to record the recognized faces against a spreadsheet of students present in a class session. It employed a face-recognition library built using dlib’s and a deep learning mechanism with an accuracy of 99.38%, OpenCV, Pandas, and web app technology, namely HTML5, CSS3, JavaScript, and python/flask. The database design was based on the resident computer file system and a CVS file type was used to handle the row-column structure of the attendance records. The panda library was implemented to mimic a structured query language. This research paper has been able to solve the problem of proxy attendance recorded in a manual attendance system by recording the registered students’ attendance automatically as they walk into the class.
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spelling intimal-16632025-07-24T01:43:24Z http://eprints.intimal.edu.my/1663/ Class-based Digital Attendance Management System with Computer Vision Ngonadi, Ifeoma V. Ajiroghene, Sunday QA75 Electronic computers. Computer science QA76 Computer software Attendance taking is an age long practice used to validate a student’s presence in class. The traditional attendance system is done with pen and paper where students write their names on the attendance sheet. This method is marred with a lot of irregularities, inefficiencies and proxy attendance(s) where students record attendance for their friends and classmates who are not present in class. This paper, therefore, develops an attendance management system that leverages on computer vision technology to detect and recognize faces and a file management system to record the recognized faces against a spreadsheet of students present in a class session. It employed a face-recognition library built using dlib’s and a deep learning mechanism with an accuracy of 99.38%, OpenCV, Pandas, and web app technology, namely HTML5, CSS3, JavaScript, and python/flask. The database design was based on the resident computer file system and a CVS file type was used to handle the row-column structure of the attendance records. The panda library was implemented to mimic a structured query language. This research paper has been able to solve the problem of proxy attendance recorded in a manual attendance system by recording the registered students’ attendance automatically as they walk into the class. INTI International University 2022-08 Article PeerReviewed text en cc_by_4 http://eprints.intimal.edu.my/1663/1/ij2022_27r.pdf text en cc_by_4 http://eprints.intimal.edu.my/1663/2/165 Ngonadi, Ifeoma V. and Ajiroghene, Sunday (2022) Class-based Digital Attendance Management System with Computer Vision. INTI JOURNAL, 2022 (27). pp. 1-9. ISSN e2600-7320 https://intijournal.intimal.edu.my/intijournal.htm
spellingShingle QA75 Electronic computers. Computer science
QA76 Computer software
Ngonadi, Ifeoma V.
Ajiroghene, Sunday
Class-based Digital Attendance Management System with Computer Vision
title Class-based Digital Attendance Management System with Computer Vision
title_full Class-based Digital Attendance Management System with Computer Vision
title_fullStr Class-based Digital Attendance Management System with Computer Vision
title_full_unstemmed Class-based Digital Attendance Management System with Computer Vision
title_short Class-based Digital Attendance Management System with Computer Vision
title_sort class-based digital attendance management system with computer vision
topic QA75 Electronic computers. Computer science
QA76 Computer software
url http://eprints.intimal.edu.my/1663/
http://eprints.intimal.edu.my/1663/
http://eprints.intimal.edu.my/1663/1/ij2022_27r.pdf
http://eprints.intimal.edu.my/1663/2/165