The resolution of the asphalt pavement disease image which collected by the CCD is too high and the area of the effective area containing information is small. A region segmentation algorithm for asphalt pavement disease image based on image content was proposed to eliminate the invalid region in the pavement image. Firstly, the original image was processed into a binary image containing the disease characteristics through a process of preprocessing and disease extraction. Then the initial traversal direction is obtained by calculating the up-to-down ratio and the left-to-right ratio of the pixels which contain information in the whole image, and counting the total number of information pixel of each row (or column). Finally, traversing from the initial traversal direction and discarding the row (or column) with the least amount of information in order to finally obtain the segmented image. In order to verify the validity and rationality of the algorithm, the image information entropy was used as the algorithm evaluation standard and compared with the traditional algorithm. The experimental results show that the proposed algorithm can keep the target information very well on the premise of effectively reducing the image resolution, and improve image information entropy.