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A shape context based Hausdorff similarity measure in image matching 会议论文  OAI收割
5th International Symposium on Photoelectronic Detection and Imaging (ISPDI) - Infrared Imaging and Applications, Beijing, June 25-27, 2013
作者:  
Ma TL(马天磊);  Liu YP(刘云鹏);  Shi ZL(史泽林);  Yin J(尹健)
收藏  |  浏览/下载:36/0  |  提交时间:2013/12/26
The traditional Hausdorff measure, which uses Euclidean distance metric (L2 norm) to define the distance between coordinates of any two points, has poor performance in the presence of the rotation and scale change although it is robust to the noise and occlusion. To address the problem, we define a novel similarity function including two parts in this paper. The first part is Hausdorff distance between shapes which is calculated by exploiting shape context that is rotation and scale invariant as the distance metric. The second part is the cost of matching between centroids. Unlike the traditional method, we use the centroid as reference point to obtain its shape context that embodies global information of the shape. Experiment results demonstrate that the function value between shapes is rotation and scale invariant and the matching accuracy of our algorithm is higher than that of previously proposed algorithm on the MEPG-7 database.  
遥感影像边缘增强的L_2向量空间范数算法 期刊论文  OAI收割
武汉大学学报(信息科学版), 2006, 期号: 6, 页码: 489-491
陈雪; 马建文
收藏  |  浏览/下载:11/0  |  提交时间:2015/01/05