Open AccessFace recognition system with PCA-GA algorithm for smart home door security using Rasberry Pi
Author(s) -
Subiyanto Subiyanto,
Dina Priliyana,
Moh. Eki Riyadani,
Nur Iksan,
Hari Wibawanto
Publication year - 2020
Publication title -
jurnal teknologi dan sistem komputer
Language(s) - English
Resource type - Journals
eISSN - 2620-4002
pISSN - 2338-0403
DOI - 10.14710/jtsiskom.2020.13590
Subject(s) - facial recognition system , principal component analysis , face (sociological concept) , artificial intelligence , computer science , genetic algorithm , raspberry pi , pattern recognition (psychology) , algorithm , computer vision , machine learning , embedded system , internet of things , social science , sociology
Genetic algorithm (GA) can improve the classification of the face recognition process in the principal component analysis (PCA). However, the accuracy of this algorithm for the smart home security system has not been further analyzed. This paper presents the accuracy of face recognition using PCA-GA for the smart home security system on Raspberry Pi. PCA was used as the face recognition algorithm, while GA to improve the classification performance of face image search. The PCA-GA algorithm was implemented on the Raspberry Pi. If an authorized person accesses the door of the house, the relay circuit will unlock the door. The accuracy of the system was compared to other face recognition algorithms, namely LBPH-GA and PCA. The results show that PCA-GA face recognition has an accuracy of 90 %, while PCA and LBPH-GA have 80 % and 90 %, respectively.