Abstract: Aiming at the unmanned requirements of coal mining face, a method for extracting and identifying coal rock image features based on LBP and GLCM is proposed. The LBP algorithm is used to judge the difference of the rock texture of the coal block. Then, the GLCM is used to realize the gray level co-occurrence matrix of the coal block rock image in the horizontal, right angle, 45 degrees and 135 degrees directions, and the energy, entropy value, contrast and inverse difference moment are completed. Extraction of texture feature parameters of four coal rock images such as partial moment. Experiments show that the LBP algorithm has certain efficiency in detecting the difference of local texture characteristics between coal and rock, but there are some shortcomings. The characteristic parameters of coal and rock image extracted by GLCM can be found to find the characteristic parameters suitable for coal and rock classification to increase the robustness of coal rock identification.