Corners and edges are all important image features in many vision-based areas. Corners are more reliable than edges and
much easier matched because of their sparseness, while edges contain richer scene structure-information more applicable
of 3D recognition. A new fast and robust edge-matching algorithm based on matched corners is proposed. In the
matching process, corner constraint and edge constraint are introduced. Firstly, the matched corners are used to guide the
edge matching. How to use the previously matched corners to guide and constrain edge matching is presented.
Furthermore, propagation idea is introduced to get matched edges. Secondly, edge constraint is proposed to limit the
search area in several pixels, then epipolar constraint is also used to achieve the matched points, if necessary the
correlation score will be utilized. Numerous experiments with various real images clearly show that if the two images
differences are not too severe, the benefit of integrating corner matches into the matching procedures is obvious, and the
algorithm greatly improves the speed as well as the correct matching ratio to higher than 97%.