A Multi-scale Polygonal Object Matching Method Based on MBR Combinatorial Optimization Algorithm

• Main Authors: LIU Lingjia, ZHU Daoye, ZHU Xinyan, DING Xiaohui, GUO Wei
• Format: Article
• Language: zho
• Published: Surveying and Mapping Press 2018-05-01
• Series: Acta Geodaetica et Cartographica Sinica
• Subjects: multi-scale; polygonal object matching; combinatorial algorithm; spatial district; artificial neural network
• Online Access: http://html.rhhz.net/CHXB/html/2018-5-652.htm

Aiming to solving the problem of positional discrepancy of corresponding objects in multi-scale polygonal object matching and that the potential matching pairs can't be directly identified by the method of areal overlapping, it is proposed that a multi-scale polygonal object matching method based on minimum bounding rectangle combinatorial optimization algorithm. The basic idea of our method is that:①identifying the potential matching pairs of 1:1, 1:<i>N</i> and <i>M</i>:<i>N</i> with combinatorial algorithm and simple shape characteristic;②establishing multi-characteristic artificial neural network model to evaluate these potential matching pairs. The proposed method is demonstrated in the experiment of matching between 1:2000 and 1:10000 polygonal objects of residential buildings and industrial facilities in Zhoushan, Zhejiang Province. The experimental results showed that the proposed matching method show superior performance against a method of area overlapping and artificial neural network. Its precision and recall are 96.5% and 89.0% under the positional discrepancy scenario, and it successfully match 1:0, 1:1,1:N and M:N matching pair.