Development of face recognition on raspberry Pi for security enhancement of smart home system

Nowadays, there is a growing interest in the smart home system using Internet of Things. One of the important aspect in the smart home system is the security capability which can simply lock and unlock the door or the gate. In this paper, we proposed a face recognition security system using Raspberr...

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Main Authors:	Gunawan, Teddy Surya, Hasan Gani, Muhammad Hamdan, Abdul Rahman, Farah Diyana, Kartiwi, Mira
Format:	Article
Language:	English English
Published:	Indonesian Journal of Electrical Engineering and Informatics (IJEEI) 2017
Subjects:	TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://irep.iium.edu.my/60142/ http://irep.iium.edu.my/60142/ http://irep.iium.edu.my/60142/ http://irep.iium.edu.my/60142/1/GunawanFaceRpi361-817-1-PB_Dec2017.pdf http://irep.iium.edu.my/60142/7/Development%20of%20face%20recognition%20on%20raspberry%20Pi%20for%20security%20enhancement%20of%20smart%20home%20system.pdf

id	iium-60142
recordtype	eprints
spelling	iium-601422018-04-18T02:17:21Z http://irep.iium.edu.my/60142/ Development of face recognition on raspberry Pi for security enhancement of smart home system Gunawan, Teddy Surya Hasan Gani, Muhammad Hamdan Abdul Rahman, Farah Diyana Kartiwi, Mira TK Electrical engineering. Electronics Nuclear engineering Nowadays, there is a growing interest in the smart home system using Internet of Things. One of the important aspect in the smart home system is the security capability which can simply lock and unlock the door or the gate. In this paper, we proposed a face recognition security system using Raspberry Pi which can be connected to the smart home system. Eigenface was used the feature extraction, while Principal Component Analysis (PCA) was used as the classifier. The output of face recognition algorithm is then connected to the relay circuit, in which it will lock or unlock the magnetic lock placed at the door. Results showed the effectiveness of our proposed system, in which we obtain around 90% face recognition accuracy. We also proposed a hierarchical image processing approach to reduce the training or testing time while improving the recognition accuracy. Indonesian Journal of Electrical Engineering and Informatics (IJEEI) 2017-12 Article PeerReviewed application/pdf en http://irep.iium.edu.my/60142/1/GunawanFaceRpi361-817-1-PB_Dec2017.pdf application/pdf en http://irep.iium.edu.my/60142/7/Development%20of%20face%20recognition%20on%20raspberry%20Pi%20for%20security%20enhancement%20of%20smart%20home%20system.pdf Gunawan, Teddy Surya and Hasan Gani, Muhammad Hamdan and Abdul Rahman, Farah Diyana and Kartiwi, Mira (2017) Development of face recognition on raspberry Pi for security enhancement of smart home system. Indonesian Journal of Electrical Engineering and Informatics (IJEEI), 5 (4). pp. 317-325. ISSN 2089-3272 http://section.iaesonline.com/index.php/IJEEI/article/view/361 10.11591/ijeei.v5i4.361
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 Gunawan, Teddy Surya Hasan Gani, Muhammad Hamdan Abdul Rahman, Farah Diyana Kartiwi, Mira Development of face recognition on raspberry Pi for security enhancement of smart home system
description	Nowadays, there is a growing interest in the smart home system using Internet of Things. One of the important aspect in the smart home system is the security capability which can simply lock and unlock the door or the gate. In this paper, we proposed a face recognition security system using Raspberry Pi which can be connected to the smart home system. Eigenface was used the feature extraction, while Principal Component Analysis (PCA) was used as the classifier. The output of face recognition algorithm is then connected to the relay circuit, in which it will lock or unlock the magnetic lock placed at the door. Results showed the effectiveness of our proposed system, in which we obtain around 90% face recognition accuracy. We also proposed a hierarchical image processing approach to reduce the training or testing time while improving the recognition accuracy.
format	Article
author	Gunawan, Teddy Surya Hasan Gani, Muhammad Hamdan Abdul Rahman, Farah Diyana Kartiwi, Mira
author_facet	Gunawan, Teddy Surya Hasan Gani, Muhammad Hamdan Abdul Rahman, Farah Diyana Kartiwi, Mira
author_sort	Gunawan, Teddy Surya
title	Development of face recognition on raspberry Pi for security enhancement of smart home system
title_short	Development of face recognition on raspberry Pi for security enhancement of smart home system
title_full	Development of face recognition on raspberry Pi for security enhancement of smart home system
title_fullStr	Development of face recognition on raspberry Pi for security enhancement of smart home system
title_full_unstemmed	Development of face recognition on raspberry Pi for security enhancement of smart home system
title_sort	development of face recognition on raspberry pi for security enhancement of smart home system
publisher	Indonesian Journal of Electrical Engineering and Informatics (IJEEI)
publishDate	2017
url	http://irep.iium.edu.my/60142/ http://irep.iium.edu.my/60142/ http://irep.iium.edu.my/60142/ http://irep.iium.edu.my/60142/1/GunawanFaceRpi361-817-1-PB_Dec2017.pdf http://irep.iium.edu.my/60142/7/Development%20of%20face%20recognition%20on%20raspberry%20Pi%20for%20security%20enhancement%20of%20smart%20home%20system.pdf
first_indexed	2023-09-18T21:25:15Z
last_indexed	2023-09-18T21:25:15Z
_version_	1777412148187627520

Development of face recognition on raspberry Pi for security enhancement of smart home system

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