TY - GEN
T1 - Correction of Temperature Estimated from a Low-Cost Handheld Infrared Camera for Clinical Monitoring
AU - Gutierrez, Evelyn
AU - Castañeda, Benjamin
AU - Treuillet, Sylvie
N1 - Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
PY - 2020
Y1 - 2020
N2 - The use of low-cost cameras for medical applications has its advantages as it enables affordable and remote evaluations of health problems; however, the accuracy is a limiting factor to use them. Previous studies indicate that parameters from object position like distance camera-object and angle of view could be used to improve temperature estimation from thermal cameras. Nevertheless, most studies are focused on expensive thermal cameras with good accuracy. In this study, an innovative experimental setup is used to study the errors associated to temperature estimation from a low-cost infrared camera: FlirOne Gen3. In our experiments, the image acquisition is done from multiple point of view (distance camera-object and viewing angles) and by using a thermal camera manipulated by hand. Then, using a regression model, a correction is proposed and tested. The results show that our proposed correction improves the temperature estimation and enhance the thermal accuracy.
AB - The use of low-cost cameras for medical applications has its advantages as it enables affordable and remote evaluations of health problems; however, the accuracy is a limiting factor to use them. Previous studies indicate that parameters from object position like distance camera-object and angle of view could be used to improve temperature estimation from thermal cameras. Nevertheless, most studies are focused on expensive thermal cameras with good accuracy. In this study, an innovative experimental setup is used to study the errors associated to temperature estimation from a low-cost infrared camera: FlirOne Gen3. In our experiments, the image acquisition is done from multiple point of view (distance camera-object and viewing angles) and by using a thermal camera manipulated by hand. Then, using a regression model, a correction is proposed and tested. The results show that our proposed correction improves the temperature estimation and enhance the thermal accuracy.
KW - Clinical thermal imaging
KW - Low-cost infrared cameras
KW - Temperature correction
UR - http://www.scopus.com/inward/record.url?scp=85080860782&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-40605-9_10
DO - 10.1007/978-3-030-40605-9_10
M3 - Conference contribution
AN - SCOPUS:85080860782
SN - 9783030406042
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 108
EP - 116
BT - Advanced Concepts for Intelligent Vision Systems - 20th International Conference, ACIVS 2020, Proceedings
A2 - Blanc-Talon, Jacques
A2 - Delmas, Patrice
A2 - Philips, Wilfried
A2 - Popescu, Dan
A2 - Scheunders, Paul
PB - Springer
T2 - 20th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2020
Y2 - 10 February 2020 through 14 February 2020
ER -