为了在不降低图象目标配准精度的前提下，加快苑配速度，提出了一种基于网格结构图象的从粗到细的目标匹配混合算法。该算法首先基本网格结构图象来抽取图象和模板的主要结构信息，以构成图象和模板的粗尺度上的一种表示，进而在这种粗尺度表示的图象上进行相似度粗匹配；然后基于引导的搜索策略，将粗匹配的目标位置对应到原图象的一些小区域，再采用部分Hausdorff距离匹配方法在这些小区域进行二次匹配和精确定位，经上述两个步骤的混合使用，不仅极大减少了计算开销，且没有降低匹配的准确度，将该混合算法与无粗匹配的部分Hausdorff距离全图匹配算法相比较，速度提高非常显著，该算法在集成电路显微图象上进行测试，取得了很好的效果。

In order to speed up object matching and location without degrading its matching accuracy in an image, this paper present a hybrid algorithm for coarse-to-fine object matching and locating method based on grid structure's image. First, the structure information of the image and template is extracted based on grid structure. The extracted information forms a coarse scale representation of the original image or the original template. On the coarse scale image some kind of similarity measure is used for matching. Then, the coarse matching position is guided to a small area of the original image by a guided searching strategy. The partial Hausdorff distance is applied to search the small area and determine the precise location in these small areas. The combination of above two steps of coarse matching and fine locating can reduces the computational cost without degrading the matching and locating accuracy. The proposed hybrid algorithm is compared to the partial Hausdorff distance matching without extracting the information of the image. The improvement of matching speed is remarkable. And the proposed algorithm is tested in integrate circuit images. It shows that the proposed matching and locating algorithm is very efficient.