An Efficient Combinatorial Algorithm for Optimal Compression of a Polyline with Segments and Arcs
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The task of finding the optimal compression of a polyline with straight-line segments and arcs is performed in many applications, such as polyline compression, noise filtering, and feature recognition. Optimal compression algorithms find the best solution using the dynamic programming approach, which requires a significant amount of arc fitting. This paper describes an improvement to the dynamic programming approach by reducing the amount of arc fitting necessary to find the optimal solution. Instead of processing from the second to the last vertices in the dynamic programming approach, the algorithm proceeds forward and skips as many steps as possible without affecting the inference in any way. Such a modification extends the practical application of the algorithm to polylines having arcs with a large number of vertices.
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