The invention discloses a method for automatically identifying pavement diseases. The method comprises the following steps of 1, converting an input pavement grey image into a binary image; 2, using a digital filter template for performing expansion processing and corrosion processing on the binary image obtained in the step 1; performing eight-communication mark on the image obtained in the step 2, obtaining the height and width of each communication area, and setting the communication area with the maximum value of the height and width smaller than the first preset threshold value to be black; 4, performing linear fitting on each communication area of the image obtained in the step 3, obtaining the length and direction vectors of a fitting line segment, obtaining the communication areas where the fitting segments with the length larger than the second preset threshold value are located, and taking the communication areas as seed areas; 5, obtaining confidence coefficients of all extended seed areas, if the maximum confidence coefficient is smaller than the confidence coefficient threshold value, judging that the diseases are not found in the pavement grey image, and if the maximum confidence coefficient is larger than a confidence coefficient threshold value, judging that the diseases are found in the pavement grey image.