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中文摘要：
为了解决强噪声干扰、部分遮挡等复杂环境下的图像匹配问题，给出了一种鲁棒的图像匹配算法。在引进圆约束的条件下，对点点间距离给出了一种新的定义。在此基础上，对经典Hausdorff距离进行改进，提出了一种新的度量，即最小最大圆度量。以此度量作为景象匹配的相似性度量，并在搜索的过程中采用圆形窗，获得了一种鲁棒的图像匹配方法，即基于最小最大圆度量的鲁棒模板匹配方法。多组实验与分析表明，该算法可以有效地解决存在旋转、灰度对比度变化、噪声干扰、部分遮挡与强光饱和等变换与干扰存在下的景象匹配定位问题。
英文摘要：
To solve the problem of image matching under complex conditions including strong noise corruption, partial occlusion etc., a robust image matching algorithm was presented. Distance between points was redefined by use of circular restriction. Based on classical Hausdorff distance and the new definition of distance, a new similarity measure, i.e., minimum maximum circular measure was defined. By applying the new measure to scene matching, and by using circular windows in the searching process, a minimum maximum circular measure based robust image matching approach was proposed. The algorithm may be used to match images with rotation, intensity contrast change, noise corruption, partial occlusion, and intensity saturation etc. The feasibility of the algorithm is analyzed theoretically, and the effectiveness of the algorithm is illustrated by multiple experiments.
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