An algorithm for automatically matching corresponding points on homonymous map features
Dongbao Zhao, Yehua Sheng, Hengliang Guo · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2008
An algorithm for automatically matching corresponding points on vector map features is put forward in this paper. Firstly, a feature simplification approach resembles Douglas-Peucker algorithm is designed to simplify geometrical entities, but here the offset threshold of Douglas-Peucker algorithm is substituted by similarity coefficient threshold defined in this paper. This approach can ensure that simplification result of map feature is invariable to similarity transformation if only the value of similarity coefficient does not change. Secondly, this algorithm extracts convex hulls of boundaries of map features which have already been simplified. Lastly, the corresponding points on the convex hulls can be recognized and matched automatically according to pre-defined matching rules. The matched corresponding points are critical points which distribute uniformly along the boundary of map feature. The experiments indicate that this algorithm is efficient and can be applied in the field of map conflation.