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Development of Face Recognition on Raspberry Pi for Security Enhancement of Smart Home System

Indonesian Journal of Electical Engineering and Informatics (IJEEI) · Vol. 5 No. 4 (2017) · hlm. 317–325

DOI
10.52549/ijeei.v5i4.361
ISSN
2089-3272, 2089-3272
Terbit
2017-12-01
Penerbit
IAES Indonesian Section
Bahasa
en

Abstrak

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.

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  • International Islamic University Malaysia
  • Yogyakarta State University
  • Syarif Hidayatullah State Islamic University Jakarta
  • Universitas Gadjah Mada
  • University of Kuala Lumpur
  • University of Indonesia
  • International Centre for Education in Islamic Finance
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Rekan penulisOrganisasiArtikel bersama
Fatchul ArifinYogyakarta State University10
Ali SophianInternational Islamic University Malaysia6
Arselan AshrafInternational Islamic University Malaysia6
Mohamed Hadi HabaebiInternational Islamic University Malaysia5
Siti Hajar YusoffInternational Islamic University Malaysia4
Hasmah MansorInternational Islamic University Malaysia4
Malik Arman MorshidiInternational Islamic University Malaysia3
Suriza Ahmad ZabidiInternational Islamic University Malaysia3
Othman Omran KhalifaInternational Islamic University Malaysia3
Noreha Abdul MalikInternational Islamic University Malaysia2
Rashidah Funke OlanrewajuInternational Islamic University Malaysia2
Aris NasuhaYogyakarta State University2
Anggun WinursitoYogyakarta State University2
Ardy Seto PriambodoYogyakarta State University2
Diyah PutrianiUniversitas Gadjah Mada2
Gairuzazmi Mat GhaniInternational Islamic University Malaysia2
Amart SulongInternational Islamic University Malaysia2
Hassan DaoUniversity of Kuala Lumpur2
Abdul MutholibInternational Islamic University Malaysia2
Intan Rahmithul Husna YaldiInternational Islamic University Malaysia2
Yasmin Mahira Saiful MunirInternational Islamic University Malaysia2
Tika ArundinaUniversity of Indonesia2
Mohd Azmi OmarInternational Centre for Education in Islamic Finance2
Nur Atikah Muhamat SalehInternational Islamic University Malaysia2
Ahmad Imran IbrahimInternational Islamic University Malaysia1
Muazzin bin RohaizatInternational Islamic University Malaysia1
W. IdrisInternational Islamic University Malaysia1
Siti Noorjannah IbrahimInternational Islamic University Malaysia1
Abdulrahman Moffaq AlawadInternational Islamic University Malaysia1
Norun Farihah Abdul MalekInternational Islamic University Malaysia1
Abd Rahman AhlanAfiliasi tidak diketahui1
A’ang SubiyaktoSyarif Hidayatullah State Islamic University Jakarta1
Husni Teja SukmanaSyarif Hidayatullah State Islamic University Jakarta1
Mir Suhail AlamInternational Islamic University Malaysia1
Didik HariyantoYogyakarta State University1
Arif Ainur RafiqPoliteknik Negeri Cilacap1

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Sumber metadata: OAI-PMH (metadata jurnal) http://section.iaesonline.com/index.php/IJEEI/oai, pertama di-harvest 8 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="en">Development of Face Recognition on Raspberry Pi for Security Enhancement of Smart Home System</dc:title>
	<dc:creator xml:lang="en">Gunawan, Teddy Surya</dc:creator>
	<dc:creator xml:lang="en">Hasan Gani, Muhammad Hamdan</dc:creator>
	<dc:creator xml:lang="en">Abdul Rahman, Farah Diyana</dc:creator>
	<dc:creator xml:lang="en">Kartiwi, Mira</dc:creator>
	<dc:subject xml:lang="en">Eigenface</dc:subject>
	<dc:subject xml:lang="en">Principal Component Analysis</dc:subject>
	<dc:subject xml:lang="en">Face recognition</dc:subject>
	<dc:subject xml:lang="en">Smart Home System.</dc:subject>
	<dc:description xml:lang="en">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.</dc:description>
	<dc:publisher xml:lang="en">IAES Indonesian Section</dc:publisher>
	<dc:date>2017-12-01</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://section.iaesonline.com/index.php/IJEEI/article/view/361</dc:identifier>
	<dc:identifier>10.52549/ijeei.v5i4.361</dc:identifier>
	<dc:source xml:lang="en">Indonesian Journal of Electrical Engineering and Informatics (IJEEI); Vol. 5 No. 4: December 2017; 317-325</dc:source>
	<dc:source>2089-3272</dc:source>
	<dc:source>2089-3272</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://section.iaesonline.com/index.php/IJEEI/article/view/361/pdf</dc:relation>
</oai_dc:dc>