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Line segment confidence region-based string matching method for map conflation

机译:基于线段置信度区域的地图匹配字符串匹配方法

摘要

In this paper, a method to detect corresponding point pairs between polygon object pairs with a string matching method based on a confidence region model of a line segment is proposed. The optimal point edit sequence to convert the contour of a target object into that of a reference object was found by the string matching method which minimizes its total error cost, and the corresponding point pairs were derived from the edit sequence. Because a significant amount of apparent positional discrepancies between corresponding objects are caused by spatial uncertainty and their confidence region models of line segments are therefore used in the above matching process, the proposed method obtained a high F-measure for finding matching pairs. We applied this method for built-up area polygon objects in a cadastral map and a topographical map. Regardless of their different mapping and representation rules and spatial uncertainties, the proposed method with a confidence level at 0.95 showed a matching result with an F-measure of 0.894.
机译:提出了一种基于线段置信区域模型的字符串匹配方法,检测多边形对象对之间的对应点对。通过字符串匹配方法找到了将目标对象的轮廓转换为参考对象的轮廓的最佳点编辑序列,该方法可以最大程度地降低其总误差成本,并从编辑序列中得出相应的点对。由于相应对象之间的明显表观位置差异是由空间不确定性引起的,因此在上述匹配过程中使用了线段的置信区域模型,因此该方法获得了较高的F值来查找匹配对。我们将此方法应用于地籍图和地形图中的建筑物区域多边形对象。不管它们的映射和表示规则如何以及空间不确定性如何,建议的置信度为0.95的方法都显示出匹配结果,F度量为0.894。

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