The problem of establishing image-to-image correspondences is fundamental in computer vision. Recently, several wide baseline matching algorithms capable of handling large changes of viewpoint have appeared. By computing feature values from image data, these algorithms mainly use appearance as a cue for matching. Topological information, i.e. spatial relations between features, has also been used, but not nearly to the same extent as appearance. In this paper, we incorporate topological constraints into an existing matching algorithm [1] which matches image intensity profiles between interest points. We show that the algorithm can be improved by exploiting the constraint that the intensity profiles around each interest point should be cyclically ordered. String matching techniques allows for an efficient implementation of the ordering constraint. Experiments with real data indicate that the modified algorithm indeed gives superior results to the original one. The method of enforcing the spatial constraints is not limited to the presented case, but can be used on any algorithm where interest point correspondences are sought.