基于空间相似性的面实体匹配算法研究

同一地物在不同来源的地图上通常存在着差异,其识别或匹配对于不同数据源的地图编制来说很关键。面状地物要素在很多地图表示中都占有很大的比例。基于人眼综合已有信息来识别同名实体的思想,本文提出了基于空间相似性的面实体匹配算法。该算法将面实体作为一个整体看待,采用加权平均法来综合面实体的位置、形状、大小等特征的相似度,进而根据获得的总相似度大小确定匹配实体。算法在确定位置相似度时选择形状中心点对面实体进行惟一标识;采用形状描述函数来计算形状相似度,不容易受各种干扰而影响精度,避免了形状信息的丢失;面实体的大小通过其覆盖面积来度量。实验结果表明该方法具有良好的稳定性和可靠性。

Areal Feature Matching Algorithm Based on Spatial Similarity

Disparities of features that represent the same real world entity from disparate sources usually occur,thus their identification or matching is crucial to map compilation.Areal features possess much in maps' representation.Motivated by the idea of identifying the same entity through integrating known information by eyes,an areal feature matching algorithm based on spatial similarity is proposed in this paper.Regarding the areal feature as a whole entity,the total similarity is obtained by integrating positional similarity,shape similarity and size similarity with a weighted average algorithm.Then the matching entities are achieved according to the maximum total similarity.The proposed algorithm identifies an areal feature by its shape-center point in order to calculate positional similarity.The shape similarity is given by the function of describing the shape,which ensures its precision not be effected by all interference and avoids the loss of shape information.Furthermore,the size of areal features is measured by its covered area.Test results show the stability and reliability of the proposed algorithm.