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

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

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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.

convolutional neural networkvisible light imagetemperature measurementlow-to-medium-range temperatures

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

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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

National Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNatural Science Foundation of Fujian Province,ChinaNatural Science Foundation of Fujian Province,ChinaNatural Science Foundation of Fujian Province,ChinaNatural Science Foundation of Fujian Province,China

61975072121741732022H00232022J02047ZZ2023J202022G02006

2024

10.1088/1674-1056/ad4cd9

中国物理B(英文版)
中国物理学会和中国科学院物理研究所

中国物理B(英文版)

CSTPCDEI
影响因子：0.995
ISSN：1674-1056
年,卷(期)：2024.33(8)