为了提高复杂变换下图模型的匹配精度，提出了一种基于有向超图的图像匹配 算法． 该算法首先分别在两个待匹配的特征点集中构造3 一致超图，计算每条超边所包含 三元组的权值，然后利用这些权值来构造加权邻接张量，最后通过凸凹松弛算法实现图像 匹配． 模拟和真实图像的实验结果表明，文中算法能够获得更高的匹配精度，对于复杂变 换的图像也有很好的匹配效果． 

An algorithm for images matching based on directed hypergraph was proposed to improve the matching accuracy of graph model under the complex transformation． Firstly，3-uniform hypergraphs in the two feature points set to be matched was constructed by the algorithm，and the weights of the triples contained in each hyperedge was calculated， then these weights were used to construct weighted adjacency tensors． Finally，image matching was achieved by convex-concave relaxation algorithm． The experiments with both simulate and real results show that the proposed algorithm can achieve higher matching accuracy and good matching effect for complex transformed images．