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

Acta Geodaetica et Cartographica Sinica

DING Xiaohui¹  ZHU Xinyan²  GUO Wei²  ZHU Daoye²  LIU Lingjia² 

[1] Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China;State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China;

关键词: multi-scale;    polygonal object matching;    combinatorial algorithm;    spatial district;    artificial neural network;   

DOI  :  10.11947/j.AGCS.2018.20160625

来源: DOAJ

【 摘 要 】

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:N and M:N 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.

【 授权许可】

Unknown