Real-time mask detection and face recognition using eigenfaces and local binary pattern histogram for attendance system

Face recognition is gaining popularity as one of the biometrics methods for an attendance system in an organization. Due to the pandemic, the common face recognition system needs to be modified to meet the current needs, whereby facemask detection is necessary. The main objective of this paper is to...

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Main Authors: Mohd Suhairi Md Suhaimin, Mohd Hanafi Ahmad Hijazi, Chung Seng Kheau, Chin Kim On
Format: Article
Language:English
English
Published: Institute of Advanced Engineering and Science (IAES) 2021
Subjects:
Online Access:https://eprints.ums.edu.my/id/eprint/30051/2/Real-time%20mask%20detection%20and%20face%20recognition%20using%20eigenfaces%20and%20local%20binary%20pattern%20histogram%20for%20attendance%20system-Abstract.pdf
https://eprints.ums.edu.my/id/eprint/30051/1/Real-time%20mask%20detection%20and%20face%20recognition%20using%20eigenfaces%20and%20local%20binary%20pattern%20histogram%20for%20attendance%20system.pdf
https://eprints.ums.edu.my/id/eprint/30051/
https://beei.org/index.php/EEI/article/view/2859/2150
https://doi.org/10.11591/eei.v10i2.2859
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spelling my.ums.eprints.300512021-07-23T03:56:36Z https://eprints.ums.edu.my/id/eprint/30051/ Real-time mask detection and face recognition using eigenfaces and local binary pattern histogram for attendance system Mohd Suhairi Md Suhaimin Mohd Hanafi Ahmad Hijazi Chung Seng Kheau Chin Kim On LB Theory and practice of education TA Engineering (General). Civil engineering (General) Face recognition is gaining popularity as one of the biometrics methods for an attendance system in an organization. Due to the pandemic, the common face recognition system needs to be modified to meet the current needs, whereby facemask detection is necessary. The main objective of this paper is to investigate and develop a real-time face recognition system for the attendance system based on the current scenarios. The proposed framework consists of face detection, mask detection, face recognition, and attendance report generation modules. The face and facemask detection is performed using the haar cascade classifier. Two techniques for face recognition were investigated, the eigenfaces and local binary pattern histogram. The initial experimental results and implementation at Kuching Community College show the effectiveness of the system. For future work, an approach that is able to perform masked face recognition will be investigated. Institute of Advanced Engineering and Science (IAES) 2021-02-20 Article PeerReviewed text en https://eprints.ums.edu.my/id/eprint/30051/2/Real-time%20mask%20detection%20and%20face%20recognition%20using%20eigenfaces%20and%20local%20binary%20pattern%20histogram%20for%20attendance%20system-Abstract.pdf text en https://eprints.ums.edu.my/id/eprint/30051/1/Real-time%20mask%20detection%20and%20face%20recognition%20using%20eigenfaces%20and%20local%20binary%20pattern%20histogram%20for%20attendance%20system.pdf Mohd Suhairi Md Suhaimin and Mohd Hanafi Ahmad Hijazi and Chung Seng Kheau and Chin Kim On (2021) Real-time mask detection and face recognition using eigenfaces and local binary pattern histogram for attendance system. Bulletin of Electrical Engineering and Informatics, 10 (2). pp. 1105-1113. ISSN 2089-3191 (P-ISSN) , 2302-9285 ( E-ISSN) https://beei.org/index.php/EEI/article/view/2859/2150 https://doi.org/10.11591/eei.v10i2.2859
institution Universiti Malaysia Sabah
building UMS Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sabah
content_source UMS Institutional Repository
url_provider http://eprints.ums.edu.my/
language English
English
topic LB Theory and practice of education
TA Engineering (General). Civil engineering (General)
spellingShingle LB Theory and practice of education
TA Engineering (General). Civil engineering (General)
Mohd Suhairi Md Suhaimin
Mohd Hanafi Ahmad Hijazi
Chung Seng Kheau
Chin Kim On
Real-time mask detection and face recognition using eigenfaces and local binary pattern histogram for attendance system
description Face recognition is gaining popularity as one of the biometrics methods for an attendance system in an organization. Due to the pandemic, the common face recognition system needs to be modified to meet the current needs, whereby facemask detection is necessary. The main objective of this paper is to investigate and develop a real-time face recognition system for the attendance system based on the current scenarios. The proposed framework consists of face detection, mask detection, face recognition, and attendance report generation modules. The face and facemask detection is performed using the haar cascade classifier. Two techniques for face recognition were investigated, the eigenfaces and local binary pattern histogram. The initial experimental results and implementation at Kuching Community College show the effectiveness of the system. For future work, an approach that is able to perform masked face recognition will be investigated.
format Article
author Mohd Suhairi Md Suhaimin
Mohd Hanafi Ahmad Hijazi
Chung Seng Kheau
Chin Kim On
author_facet Mohd Suhairi Md Suhaimin
Mohd Hanafi Ahmad Hijazi
Chung Seng Kheau
Chin Kim On
author_sort Mohd Suhairi Md Suhaimin
title Real-time mask detection and face recognition using eigenfaces and local binary pattern histogram for attendance system
title_short Real-time mask detection and face recognition using eigenfaces and local binary pattern histogram for attendance system
title_full Real-time mask detection and face recognition using eigenfaces and local binary pattern histogram for attendance system
title_fullStr Real-time mask detection and face recognition using eigenfaces and local binary pattern histogram for attendance system
title_full_unstemmed Real-time mask detection and face recognition using eigenfaces and local binary pattern histogram for attendance system
title_sort real-time mask detection and face recognition using eigenfaces and local binary pattern histogram for attendance system
publisher Institute of Advanced Engineering and Science (IAES)
publishDate 2021
url https://eprints.ums.edu.my/id/eprint/30051/2/Real-time%20mask%20detection%20and%20face%20recognition%20using%20eigenfaces%20and%20local%20binary%20pattern%20histogram%20for%20attendance%20system-Abstract.pdf
https://eprints.ums.edu.my/id/eprint/30051/1/Real-time%20mask%20detection%20and%20face%20recognition%20using%20eigenfaces%20and%20local%20binary%20pattern%20histogram%20for%20attendance%20system.pdf
https://eprints.ums.edu.my/id/eprint/30051/
https://beei.org/index.php/EEI/article/view/2859/2150
https://doi.org/10.11591/eei.v10i2.2859
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