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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Indonesian Journal of Electrical Engineering and Computer Science Jurnal Generic
Bhakti Yudho Suprapto
Universitas Sriwijaya
Computer Science & IT Electrical & Electronics Engineering Engineering

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Facial recognition and body temperature measurements based on thermal images using a deep-learning algorithm Suci Dwijayanti; Muhammad Ridho Ramadhan; Bhakti Yudho Suprapto
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 12, No 4: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v12.i4.pp1654-1665

Abstract

Recognizing the early symptoms of the SARS-CoV-2 virus (COVID-19) is essential for minimizing its spread. One of the typical symptoms of a person infected with COVID-19 is increased body temperature beyond the normal range. Facial recognition can be used to separate healthy people from those with high body temperatures based on thermal images of the faces. In this study, the XEAST XE-27 thermal imager modes 2, 3, and 4 comprising 1500 thermal images each were compared. The facial recognition was performed using a convolutional neural network. Additionally, body temperatures were extracted from thermal images using matrix laboratory (MATLAB) by considering the minimum and maximum temperatures of each mode and class. The network training results indicate that the accuracies achieved by the proposed facial recognition system in modes 2, 3, and 4 are 87.33%, 92.33%, and 91.66%, respectively. Furthermore, the accuracies of body temperature extraction in modes 2, 3, and 4 are 70%, 60%, and 40%, respectively. Thus, the proposed system serves as a contactless technique for the early detection of COVID-19 symptoms by combining facial recognition and body temperature measurements.
Co-Authors A. Wahyudin Agung Juli Anda Agus Adhi Nugroho Ahmad Zarkasi Aulia Ghaida Bustanul Arifin Deris Stiawan Eka Nuryanto Budi Susila Erliza Yuniarti Fachrudin Abdau Hera Hikmarika Huda Ubaya Muhamad Haddin Muhammad Khosyi'in Muhammad Khosyi'in Muhammad Ridho Ramadhan Osvari Arsalan Siti Nurmaini Sri Arttini Dwi Prasetyawati Sri Desy Siswanti Suci Dwijayanti Yesi Novaria Kunang Zainuddin Nawawi