为了快速高效地进行目标搜索，提出了一种在仿射变换条件下，利用Hausdroff距离进行目标搜索的高效算法。此算法是在一种新的距离变换形式——“最小正方盒距离变换”的基础上进行的。实验结果表明，与现有算法相比，该算法在不影响搜索成功率和目标定位精度的情况下，还可以显著地缩短搜索时间。为验证该算法的有效性，将该算法与Rucklidge算法进行了对比实验，结果表明，该算法明显优于Rucklidge提出的快速目标搜索算法。

The Hausdroff distance, a measure defined between two point sets, has been used to search for objects in images for its robustness and reliability. In this paper, a highly efficient approach, which uses the Hausdorff distance to locate an object that has undergone an affine transformation, is presented. Prior to our study, the most efficient methods for solving such a problem are two of Rucklidge' s methods:“without zoning" and“4×4 zoning". The proposed approach shares some similarities with Rucklidge' s methods but is mainly based on the“smallest square box distance transform" introduced in this paper. The idea of“smallest square box distance transform" is described in detail in this paper along with its implementation. By replacing the“box distance transform" of Rucklidge' s methods with our“smallest square box distance transform" in the search process, a much higher search speed can be achieved while maintaining the search success rate and target location accuracy. In all, two experiments are given in this paper. One experiment is to test the proposed approach on edge images and the other experiment is based on feature point images. It can be seen from the experimental results of both experiments that the proposed approach apparently outperforms Rucklidge's fast methods.