To solve the problem of the registration position deviation for multi-repeat texture images，a double-match image registration （DMIR） algorithm is proposed. The DMIR algorithm not only considers the matching result of one graph with another graph，but also considers the matching result of a graph with its own features. Firstly，the key points are matched by the K-nearest neighbor （KNN） algorithm after extracting the feature points by the scale-invariant feature transform （SIFT） algorithm. As a result，the self-matching point pairs of the same image and the initial matching point pairs between different images are obtained respectively. Secondly，the best matching point pairs are obtained by computing the correlation between different points of the initial matching point pairs. Thirdly，the correct matching point pairs of the two images are determined，which depend on the positional relationship between the best matching point pairs and the self-matching point pairs. Lastly，the affine matrix is calculated according to the matching point pairs，and the image stitching is performed. The experimental results show that the matching point pairs obtained by the DMIR algorithm are more accurate， and the stitched images are better than others.