In view of the matching problem of low texture objects, a line matching algorithm based on local neighboring gradient information and global structural information was proposed. The mean standard deviation line descriptor was redesigned to get the initial matching; the global topological structure between lines was used to get rid of wrong matches; more matches were achieved by utilizing the iterative topological filter. Moreover, global angle constrains were implemented to make the algorithm more efficient and to further remove wrong matches. Experiments show that the proposed algorithm is highly robust under various image changes including heavy illumination change, image rotation, image blur, scale change as well as viewpoint change and is much better than the other two popular methods in terms of matching accuracy and efficiency.