Many photogrammetric procedures, such as orientation of stereopairs, aerial triangulation, and DEM generation, depend on image matching. Most of the work related to matching shapes in digital photogrammetry utilizes parameterized shapes, where shapes are approximated by analytical functions or polygons. In this paper a general matching algorithm is proposed based on the principles of Generalized Hough Transform (GHT). It utilizes non-parameterized shapes and does not require a polygonal approximation nor does it depend on curve breakpoints. An approach is also proposed for rotation and scale invariant GHT in order to enable dealing with stereopair images that have rotation and/or scale change between them.
In the proposed matching algorithm edge segments are extracted in the overlapping images using Canny edge detector and an edge tracking algorithm. The matching procedure is applied for each edge segment in one image against its matching candidates in the other image. A consistency check for the matching results is performed utilizing the relationship among edge segments in both images. Results showed the efficiency of the matching approach in dealing with broken and occluded edge segments and in achieving good and robust results.
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