Open AccessAccurate detection method of pig's temperature based on non‐point source thermal infrared image
Author(s) -
Zhang Zaiqin,
Wang Hao,
Liu Tonghai,
Wang Yueqiang,
Zhang Hang,
Yuan Feiyan,
Yang Xue,
Xu Shunlai,
Meng Yuhuan
Publication year - 2021
Publication title -
caai transactions on intelligence technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.613
H-Index - 15
ISSN - 2468-2322
DOI - 10.1049/cit2.12017
Subject(s) - infrared , grayscale , body surface , pixel , thermal infrared , mean squared error , population , temperature measurement , artificial intelligence , mathematics , materials science , computer science , optics , statistics , physics , geometry , demography , quantum mechanics , sociology
Body temperature measurement is a very important task in the sow breeding process. The authors used an infrared camera to detect the temperature of the body surface of the sows, relying on calculating the average of the infrared image temperature in the ear root region. Based on the grayscale value of the target image of the infrared image and the corresponding temperature value of 180 infrared images, a G‐T (Gray‐Temperature ) model was established by linear least squares method, which achieved temperature inversion of each pixel of the target pig. For the different growth stages and different breeds of sows, the R‐square of the all established models is greater than 0.95. The average relative error of the model inversion of the body temperature was only 0.076977%. This means that the body temperature of the sows could be detected without relying on the software. Based on the G‐T model, the authors design a kind of sow's ear root recognition and body surface temperature detection algorithm for different sow population scenarios.