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Feature matching algorithm based on spatial similarity

机译:基于空间相似度的特征匹配算法

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摘要

The disparities of features that represent the same real world entities from disparate sources usually occur, thus the identification or matching of features is crutial to the map conflation. Motivated by the idea of identifying the same entities through integrating known information by eyes, the feature matching algorithm based on spatial similarity is proposed in this paper. Total similarity is obtained by integrating positional similarity, shape similarity and size similarity with a weighted average algorithm, then the matching entities is achieved according to the maximum total similarity. The matching of areal features is analyzed in detail. Regarding the areal feature as a whole, the proposed algorithm identifies the same areal features by their shape-center points in order to calculate their positional similarity, and shape similarity is given by the function of describing the shape, which ensures its precision not be affected by interferes and avoids the loss of shape information, furthermore the size of areal features is measured by their covered areas. Test results show the stability and reliability of the proposed algorithm, and its precision and recall are higher than other matching algorithm.
机译:来自不同来源的代表相同真实世界实体的特征差异通常会发生,因此,特征的识别或匹配对于地图合并至关重要。本文提出了一种基于空间相似度的特征匹配算法。通过将位置相似度,形状相似度和大小相似度与加权平均算法相结合,得到总相似度,然后根据最大总相似度获得匹配实体。详细分析区域特征的匹配。对于整个区域特征,该算法通过形状中心点识别相同的区域特征以计算其位置相似度,并通过描述形状的功能赋予形状相似度,从而确保其精度不受影响。通过干涉并避免形状信息的丢失,此外,通过覆盖区域来测量区域特征的大小。实验结果表明,该算法具有稳定性和可靠性,其精度和召回率均高于其他匹配算法。

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