Computing the minimum Hausdorff distance for point sets under translation

SCG '90 Pub Date : 1990-05-01 DOI:10.1145/98524.98599
D. Huttenlocher, K. Kedem
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引用次数: 141

Abstract

We consider the problem of computing a translation that minimizes the Hausdorff distance between two sets of points. For points in @@@@1 in the worst case there are ⊖(mn) translations at which the Hausdorff distance is a local minimum, where m is the number of points in one set and n is the number in the other. For points in @@@@2 there are ⊖(mn(m + n)) such local minima. We show how to compute the minimal Hausdorff distance in time &Ogr;(mn log mn) for points in @@@@1 and in time &Ogr;(m2n2α(mn)) for points in @@@@2. The results for the one-dimensional case are applied to the problem of comparing polygons under general affine transformations, where we extend the recent results of Arkin et al on polygon resemblance under rigid body motion. The two-dimensional case is closely related to the problem of finding an approximate congruence between two points sets under translation in the plane, as considered by Alt et al.
计算平移下点集的最小豪斯多夫距离
我们考虑计算使两组点之间的豪斯多夫距离最小化的平移问题。对于@@@@1中的点,在最坏的情况下,有几个平移(mn),其中Hausdorff距离是局部最小值,其中m是一个集合中的点的数量,n是另一个集合中的点的数量。对于@@@@2中的点,存在这样的局部极小值(mn(m + n))。我们展示了如何计算@@@@1中点在时间&Ogr;(mn log mn)和@@@@2中点在时间&Ogr;(m2n2α(mn))中的最小豪斯多夫距离。将一维情况下的结果应用于一般仿射变换下多边形的比较问题,推广了Arkin等人关于刚体运动下多边形相似性的最新结果。二维情况与Alt等人在平面上平移的两个点集之间寻找近似同余的问题密切相关。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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