PENGENALAN CITRA WAJAH DAN IDENTIFIKASI SUHU TUBUH DENGAN CITRA TERMAL MENGGUNAKAN ALGORITMA DEEP LEARNING

RAMADHAN, M. RIDHO and Dwijayanti, Suci (2021) PENGENALAN CITRA WAJAH DAN IDENTIFIKASI SUHU TUBUH DENGAN CITRA TERMAL MENGGUNAKAN ALGORITMA DEEP LEARNING. Undergraduate thesis, Sriwijaya University.

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Abstract

Body temperature is a symptom that can be used to indicate someone suffered from COVID-19 when his temperature exceeds the normal temperature. To ease the separation of groups of health people from those who are above normal temperature, face recognition can be used to recognize someone contactless. Thermal image of face can be used as an approach to not only perform face recognition, but also obtain the body temperature. This study compares the XEAST XE-27 thermal imager modes used, namely mode 2, mode 3 and mode 4. The number of thermal images used in this research were 1500 images for each thermal imager mode. Face recognition process was performed using a convolutional neural network (CNN). Meanwhile, the process of extracting body temperature from thermal images was performed using the minimum and maximum temperature of each mode and class. Based on the results of the trained network, the best architecture model of CNN is using 64 filters, 5x5 kernel size, mean squared error (MSE) as loss function, learning rate 0.001 dan root mean square propagation (RMSprop) as optimizer. The accuracy result of the face recognition system in mode 2, mode 3 and mode 4 are 86,67%, 91,33% and 94,33%, respectively. While, the accuracy of body temperature extraction in mode 2, mode 3, and mode 4 were 70%, 60% and 40%, respectively. This result shows that thermal images can be used to know the body temperature and CNN can recognize person’s identity through the thermal image.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Citra Termal, CNN, Face Recognition, Suhu Tubuh
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK1-9971 Electrical engineering. Electronics. Nuclear engineering > TK1 Electrical engineering--Periodicals. Automatic control--Periodicals. Computer science--Periodicals. Information technology--Periodicals. Automatic control. Computer science. Electrical engineering. Information technology. T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7885-7895 Computer engineering. Computer hardware
Divisions:	03-Faculty of Engineering > 20201-Electrical Engineering (S1)
Depositing User:	M. Ridho Ramadhan
Date Deposited:	02 Aug 2021 07:12
Last Modified:	02 Aug 2021 07:12
URI:	http://repository.unsri.ac.id/id/eprint/51106

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