Deep learning-assisted common temperature measurement based on visible light imaging  

作　　者：朱佳仪 何志民 黄成 曾峻 林惠川 陈福昌 余超群 李燕 张永涛 陈焕庭 蒲继雄 Jia-Yi Zhu;Zhi-Min He;Cheng Huang;Jun Zeng;Hui-Chuan Lin;Fu-Chang Chen;Chao-Qun Yu;Yan Li;Yong-Tao Zhang;Huan-Ting Chen;Ji-Xiong Pu(College of Physics and Information Engineering,Minnan Normal University,Zhangzhou 363000,China;Fujian Provincial Key Laboratory of Light Propagation and Transformation,College of Information Science&Engineering,Huaqiao University,Xiamen 361021,China)

机构地区：[1]College of Physics and Information Engineering,Minnan Normal University,Zhangzhou 363000,China [2]Fujian Provincial Key Laboratory of Light Propagation and Transformation,College of Information Science&Engineering,Huaqiao University,Xiamen 361021,China

出　　处：《Chinese Physics B》2024年第8期230-236,共7页中国物理B（英文版）

基　　金：Project supported by the National Natural Science Foundation of China (Grant Nos.61975072 and 12174173);the Natural Science Foundation of Fujian Province,China (Grant Nos.2022H0023,2022J02047,ZZ2023J20,and 2022G02006)。

摘　　要：Real-time,contact-free temperature monitoring of low to medium range(30℃-150℃)has been extensively used in industry and agriculture,which is usually realized by costly infrared temperature detection methods.This paper proposes an alternative approach of extracting temperature information in real time from the visible light images of the monitoring target using a convolutional neural network(CNN).A mean-square error of<1.119℃was reached in the temperature measurements of low to medium range using the CNN and the visible light images.Imaging angle and imaging distance do not affect the temperature detection using visible optical images by the CNN.Moreover,the CNN has a certain illuminance generalization ability capable of detection temperature information from the images which were collected under different illuminance and were not used for training.Compared to the conventional machine learning algorithms mentioned in the recent literatures,this real-time,contact-free temperature measurement approach that does not require any further image processing operations facilitates temperature monitoring applications in the industrial and civil fields.

关 键 词：convolutional neural network visible light image temperature measurement low-to-medium-range temperatures 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] TP391.41[自动化与计算机技术—控制科学与工程]