An　optimal　correspondence　model　was　proposed　for　solving　image　matching　problems　with　multi-order　features.　A　multi-order　feature　of　an　image　refers　to　any　of　its　first-,　second-and　third-order　feature,　which　was　defined　by　a　simple　feature　point,　an　edge　linking　two　feature　points　and　a　triangle　connecting　three　feature　points,　respectively.　The　optimal　correspondence　model　was　a　weighted　bipartite　graph　with　multi-order　feature　as　its　vertex.　With　this　model　the　weight　could　be　directly　computed　and　the　solution　can　be　easily　obtained　by　the　Kuhn-Munkras　algorithm.　Results　show　that　the　model　has　good　robustness　for　video　sequence　and　graffiti　images.　Even　with　obvious　rotation,　scale,　and　affine　transformation,　it　can　produce　a　relatively　accurate　correspondence　result,　which　is　usually　better　than　the　famous　Flann　and　BruteForce　algorithms　in　OpenCV.