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In order to solve the problem of insufficient accuracy in evaluating the feather coverage of laying hens by using manual and temperature threshold segmentation methods, thermal infrared images and color images approaches were proposed to calculate the feather coverage. By using Otsu algorithm combined with different color models to extract the chicken body target and the well-covered area of the back feathers and calculate the area ratio, the coverage of the back feathers was obtained. Aiming at the problem of poor segmentation effect caused by the blurred edge of the target chicken body in thermal infrared images, an adaptive thermal infrared image enhancement method based on the gray histogram of R and B components was proposed. The experimental results showed that the segmentation accuracy of chicken body targets and well-covered areas with feathers in thermal infrared images reached 97.18% and 96.86%, and the segmentation accuracy of color images reached 99.58% and 97.86%. The calculation result of the thermal infrared images was closer to the real value of feather coverage than that of color images. The analysis revealed that the roots of white feathers exposed by behaviors of laying hens rubbing against the chicken coop were the main factors for the deviation of the coverage results of the color image calculation. Feather coverage affected chicken body surface temperature. The results showed that the chicken body feather coverage was significantly negatively correlated with the body surface temperature (P<0.01), and the average temperature of the damaged area of the same level was 10℃ higher than the average temperature of the back.