摘要
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,可用于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.
出处
《中国图象图形学报》
CSCD
北大核心
2006年第11期1661-1664,共4页
Journal of Image and Graphics
基金
新型显示技术及应用集成教育部重点实验室开放课题基金项目(P200501)
上海市重点学科实验室基金项目(T0102)
