ing at the problem of low registration rate in image feature point extraction and matching algorithm, an image registration algorithm is proposed to optimize the grid motion statistics. The algorithm first uses oriented fast and rotated brief algorithm to extract the feature points, and then rough feature point registration is carried out by Brute-Force matching algorithm. According to the size of the image and the number of feature points, the image is divided into multiple grids, and the number of feature points in the grid is moved for statistics. A score statistics template is created by using Gaussian function through the distance between the nine-square grid feature points and the central feature points. The score statistics of the nine-square grid is compared with the set threshold. If the threshold is exceeded, it is considered to be a correct matching point, otherwise it will be filtered out. Experimental results show that the number of exact matching points between the proposed algorithm and the grid-based motion statistics algorithm is increased by 18.17%, and the speed can be increased by about 41.3% compared with the traditional feature point extraction matching algorithm. This method can effectively eliminate false matches and improve the matching rate.