Feature Matching from Network Data at Different Scales Based on Similarity Measure

An algorithm for feature matching from network data at different map scaled based on similarity measure is presented.The whole strategy of matching is the first pre-matching of nodes and arcs,followed by accurate matching through similarity of node-arc topologies and discrete Fréchet distance.The matching process combines the matches in geometry,semantics,topology,nodes and arcs effectively.Finally,the different matching results are displayed to facilitate the human-computer interaction.The experimental results show that this method can match correspondent roads under complicated conditions effectively,and heighten the correctness and the speed of the feature matching.