形状匹配算法虽然在基于内容的视频检索中应用广泛，但由于视频数据量非常大，匹配非常耗时，因此形状匹配算法通常会成为实时视频检索的瓶颈，为了快速准确地进行形状匹配和检索，提出了一种改进的多分辨率Hausdorff距离变换算法，该算法是通过对后向匹配算法进行优化来使匹配速度大大加速，可用干进行实时车型比较和识别。实验结果表明，该改进算法在车型识别上具有速度快和准确性高的优点，尤其在模板图像比较大的情况下，此改进算法优势明显。

Shape matching algorithm is widely used in many applications of the content-based retrieval, however, due to large data amount of the video stream and the computation of processing, the shape matching algorithm always become bottleneck in the real-time video retrieval. In this paper, we propose an improved algorithm for Hausdorff distance based on multi-resolution, supposed to be applied in the real-time vehicle comparison and recognition, the backward matching algorithm has a great optimization. Experimental resuh shows that the algorithm makes vehicle recognition more fast and accurate, expecially when the model image is big, this improved algorithm has a larger excellence.