基于拟Laplacian谱和点对拓扑特征的点模式匹配算法  

Algorithm of point pattern matching based on quasi Laplacian spectrum and point pair topological characteristics

作　　者：张官亮[1,2] 邹焕新[1] 卢春燕[1] 赵键[1] 

机构地区：[1]国防科学技术大学电子科学与工程学院,长沙410073 [2]武警乌鲁木齐指挥学院教研部,乌鲁木齐830049

出　　处：《计算机应用》2013年第6期1686-1690,共5页journal of Computer Applications

摘　　要：针对谱匹配方法对噪声和出格点的鲁棒性较差的问题,提出了一种基于拟Laplacian谱和点对拓扑特征的点模式匹配算法。首先,用赋权图的最小生成树构造无符号Laplacian矩阵,通过对矩阵谱分解得到的特征值和特征向量表示点的特征,进而计算点的初始匹配概率;其次,利用点对拓扑特征的相似性测度来定义点对间的局部相容性,然后借助概率松弛的方法更新由拟Laplacian谱得到的匹配概率,得出匹配结果。对比实验结果表明,该方法在处理存在噪声和出格点的点集匹配上具有较高的鲁棒性。Concerning the poor robustness of the state-of-art spectrum-based algorithms when the outliers and noises exist, a new and robust point pattern matching algorithm based on Quasi Laplacian spectrum and Point Pair Topological Characteristic （QL-PPTC） was proposed. In this paper, firstly, a signless Laplacian matrix was constructed by using the minimal spanning tree of weighted graph, and then the eigenvalues and eigenvectors obtained from the spectrum decomposition were used to represent the point＇ s feature, which made it possible to calculate the matching probability. Secondly, the similarity measurement of point pair topological characteristic was computed to define local compatibility between the point pairs, and then correct matching results were achieved by using the method of probabilistic relaxation. The contrast experimental results show that the proposed algorithm is robust when the outliers and noises exist in point matching.

关 键 词：点模式匹配 最小生成树 拟Laplacian谱 相似性测度 点对拓扑特征 概率松弛 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]