一种用于目标匹配的改进Hausdorff距离

Marie-Pierre Dubuisson, Anil K. Jain
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引用次数: 1504

摘要

对象匹配的目的是确定两个对象之间的相似度。本文介绍了基于两个点集之间的豪斯多夫距离的24种可能的距离度量。这些方法可以用来匹配从任意两个物体中提取的两组边缘点。基于对包含不同程度噪声的合成图像的实验,作者确定了其中一种称为修正豪斯多夫距离(MHD)的距离度量在目标匹配方面具有最佳性能。MHD在其他距离上的优势也在从真实图像中提取的物体的几个边缘快照上得到了证明。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A modified Hausdorff distance for object matching
The purpose of object matching is to decide the similarity between two objects. This paper introduces 24 possible distance measures based on the Hausdorff distance between two point sets. These measures can be used to match two sets of edge points extracted from any two objects. Based on experiments on synthetic images containing various levels of noise, the authors determined that one of these distance measures, called the modified Hausdorff distance (MHD) has the best performance for object matching. The advantages of MHD ever other distances are also demonstrated on several edge snaps of objects extracted from real images.
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