Improved Approximation Bounds for Planar Point Pattern Matching

被引:0
|
作者
Minkyoung Cho
David M. Mount
机构
[1] University of Maryland,Department of Computer Science
[2] University of Maryland,Department of Computer Science and Institute for Advanced Computer Studies
来源
Algorithmica | 2008年 / 50卷
关键词
Point pattern matching; Approximation algorithms; Hausdorff distance;
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中图分类号
学科分类号
摘要
We analyze the performance of simple algorithms for matching two planar point sets under rigid transformations so as to minimize the directed Hausdorff distance between the sets. This is a well studied problem in computational geometry. Goodrich, Mitchell, and Orletsky presented a very simple approximation algorithm for this problem, which computes transformations based on aligning pairs of points. They showed that their algorithm achieves an approximation ratio of 4. We introduce a modification to their algorithm, which is based on aligning midpoints rather than endpoints. This modification has the same simplicity and running time as theirs, and we show that it achieves a better approximation ratio of roughly 3.14. We also analyze the approximation ratio in terms of a instance-specific parameter that is based on the ratio between diameter of the pattern set to the optimum Hausdorff distance. We show that as this ratio increases (as is common in practical applications) the approximation ratio approaches 3 in the limit. We also investigate the performance of the algorithm by Goodrich et al. as a function of this ratio, and present nearly matching lower bounds on the approximation ratios of both algorithms.
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页码:175 / 207
页数:32
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