The maximum temperature of the dairy cow’s eye area is highly correlated with the widely used rectal temperature. The existing methods have not been able to automatically extract the eye temperature from the thermal infrared image. In order to achieve non-contact, automatic and high-precision detection of dairy cow’s eye temperature, a method for automatic detection of dairy cow’s eye temperature based on thermal infrared imaging technology and skeleton tree model was studied and proposed. On the basis of the thermal infrared image of the side of dairy cow, the threshold segmentation method based on the gap measurement was used to extract the dairy cow target, and the precise extraction of the dairy cow skeleton was realized and the dairy cow skeleton tree model was constructed. In this model, the head area of dairy cattle was accurately located, and then according to the shape characteristics of the head outline and the geometric position characteristics of the eyes, the center point of the eye area of dairy cattle was accurately located. Finally, the eye temperature was automatically detected in the thermal infrared image of dairy cow with the center point of the eye as the center and the highest temperature in the 20 pixels radius area as the eye temperature. In order to verify the effectiveness of this method, totally 100 thermal infrared images from 50 dairy cows were randomly selected for the test. The results showed that the average absolute error of eye temperature was 0.35℃, and the average relative error was 0.38%. The method had high accuracy and can provide technical support for the non-contact, automatic and high-precision detection of dairy cow temperature.