Accurate detection method of pig's temperature based on non‐point source thermal infrared image

• Main Authors: Zaiqin Zhang, Hao Wang, Tonghai Liu, Yueqiang Wang, Hang Zhang, Feiyan Yuan, Xue Yang, Shunlai Xu, Yuhuan Meng
• Format: Article
• Language: English
• Published: Wiley 2021-09-01
• Series: CAAI Transactions on Intelligence Technology
• Online Access: https://doi.org/10.1049/cit2.12017

Abstract 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.