Rice lodging refers to the phenomenon that rice crops growing upright are skewed and even the whole plant falls to the ground due to the influence of external forces. When the paddy field that has fallen down is harvested mechanically, it is necessary to adjust the harvesting direction, the height of the header and other factors according to the specific lodging situation. In the rice field image taken from the driving perspective of the harvester, the texture feature of the rice field image in the harvest area will rise or fall rapidly and shake greatly due to the lodging of part of the rice. In this paper, the gray level co-occurrence matrix analysis method and MATLAB simulation tools are used to analyze the texture characteristics of the four main factors of Angular Second Moment, Correlation, Inverse Different Moment and Contrast in the image of the area to be harvested from the driving perspective of the harvester. It provides a basis for determining the texture feature parameter criterion when using the neural network to detect the lodging situation of rice.