Class attendance management system using face recognition

We are living in a world where everything is automated and linked online. The internet of things, image processing, and machine learning are evolving day by day. Many systems have been completely changed due to this evolve to achieve more accurate results. The attendance system is a typicalexample o...

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Main Authors:	Abdul Rhman Salim, Omar, Olanrewaju, Rashidah Funke, Balogun, Wasiu Adebayo
Format:	Conference or Workshop Item
Language:	English English
Published:	Institute of Electrical and Electronics Engineers Inc. 2018
Subjects:	TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://irep.iium.edu.my/70809/ http://irep.iium.edu.my/70809/ http://irep.iium.edu.my/70809/ http://irep.iium.edu.my/70809/1/70809_Class%20attendance%20management%20system_SCOPUS.pdf http://irep.iium.edu.my/70809/7/70809_Class%20attendance%20management%20system%20using%20face%20recognition.pdf

id	iium-70809
recordtype	eprints
spelling	iium-708092019-02-19T07:30:00Z http://irep.iium.edu.my/70809/ Class attendance management system using face recognition Abdul Rhman Salim, Omar Olanrewaju, Rashidah Funke Balogun, Wasiu Adebayo TK Electrical engineering. Electronics Nuclear engineering We are living in a world where everything is automated and linked online. The internet of things, image processing, and machine learning are evolving day by day. Many systems have been completely changed due to this evolve to achieve more accurate results. The attendance system is a typicalexample of this transition, starting from the traditional signature on a paper sheet to face recognition. This paper proposes a method of developing a comprehensive embedded class attendance systemusing facial recognition with controlling the door access. The system is based on Raspberry Pi thatruns Raspbian (Linux) Operating System installed on micro SD card. The Raspberry Pi Camera, as well as a 5-inch screen, are connected to the Raspberry Pi. By facing the camera, the camera will capture the image then pass it to the Raspberry Pi which is programmed to handle the face recognition by implementing the Local Binary Patterns algorithm LBPs. If the student's input image matches withthetrained dataset image the prototype door will open using Servo Motor, then the attendance results will be stored in the MySQL database. The database is connected to Attendance Management Syste(AMS) web server, which makes the attendance results reachable to any online connected web browser.The system has 95{\% accuracy with the dataset of 11 person images. Institute of Electrical and Electronics Engineers Inc. 2018 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/70809/1/70809_Class%20attendance%20management%20system_SCOPUS.pdf application/pdf en http://irep.iium.edu.my/70809/7/70809_Class%20attendance%20management%20system%20using%20face%20recognition.pdf Abdul Rhman Salim, Omar and Olanrewaju, Rashidah Funke and Balogun, Wasiu Adebayo (2018) Class attendance management system using face recognition. In: 7th International Conference on Computer and Communication Engineering, ICCCE 2018, 19th-20th September 2018, Kuala Lumpur, Malaysia. https://ieeexplore.ieee.org/document/8539274 10.1109/ICCCE.2018.8539274
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English
topic	TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	TK Electrical engineering. Electronics Nuclear engineering Abdul Rhman Salim, Omar Olanrewaju, Rashidah Funke Balogun, Wasiu Adebayo Class attendance management system using face recognition
description	We are living in a world where everything is automated and linked online. The internet of things, image processing, and machine learning are evolving day by day. Many systems have been completely changed due to this evolve to achieve more accurate results. The attendance system is a typicalexample of this transition, starting from the traditional signature on a paper sheet to face recognition. This paper proposes a method of developing a comprehensive embedded class attendance systemusing facial recognition with controlling the door access. The system is based on Raspberry Pi thatruns Raspbian (Linux) Operating System installed on micro SD card. The Raspberry Pi Camera, as well as a 5-inch screen, are connected to the Raspberry Pi. By facing the camera, the camera will capture the image then pass it to the Raspberry Pi which is programmed to handle the face recognition by implementing the Local Binary Patterns algorithm LBPs. If the student's input image matches withthetrained dataset image the prototype door will open using Servo Motor, then the attendance results will be stored in the MySQL database. The database is connected to Attendance Management Syste(AMS) web server, which makes the attendance results reachable to any online connected web browser.The system has 95{\% accuracy with the dataset of 11 person images.
format	Conference or Workshop Item
author	Abdul Rhman Salim, Omar Olanrewaju, Rashidah Funke Balogun, Wasiu Adebayo
author_facet	Abdul Rhman Salim, Omar Olanrewaju, Rashidah Funke Balogun, Wasiu Adebayo
author_sort	Abdul Rhman Salim, Omar
title	Class attendance management system using face recognition
title_short	Class attendance management system using face recognition
title_full	Class attendance management system using face recognition
title_fullStr	Class attendance management system using face recognition
title_full_unstemmed	Class attendance management system using face recognition
title_sort	class attendance management system using face recognition
publisher	Institute of Electrical and Electronics Engineers Inc.
publishDate	2018
url	http://irep.iium.edu.my/70809/ http://irep.iium.edu.my/70809/ http://irep.iium.edu.my/70809/ http://irep.iium.edu.my/70809/1/70809_Class%20attendance%20management%20system_SCOPUS.pdf http://irep.iium.edu.my/70809/7/70809_Class%20attendance%20management%20system%20using%20face%20recognition.pdf
first_indexed	2023-09-18T21:40:31Z
last_indexed	2023-09-18T21:40:31Z
_version_	1777413108586774528

Class attendance management system using face recognition

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