Triangulation of well-defined points as a constraint for reliable image matching

This study demonstrates the utilization of the well-defined points to improve the reliability and accuracy of image matching. The basic principle is: (a) to triangulate a few well-defined points within the stereo model area to form a coarse triangulation; (b) to detect certain amount of corners within each triangle for further matching; (c) to propagate the matching of corner points from the reference points (i.e., the three triangle vertices) to obtain the best matching for each of these corners; (d) to dynamically update the triangulation by inserting the newly matched corner; and (e) to further detect corners and perform matching for them until a pre-defined criteria (the minimum size of triangle or the largest number of points matched) is reached. Experimental results reveal: (a) the false matching caused by the occlusion and repetitive texture is diminished; (b) the accuracy is improved, i.e., with a reduction of RMSE of check points (located in different types of terrain areas) by 12 percent to 62 percent, and a reduction of the largest error by up to two times; and (c) most building corners and boundary points of main objects could be matched directly and accurately.