当两个要匹配的点模式不同构时，以谱方法为基础的点模式匹配算法性能较差。为了提高谱方法对非同构点模式的匹配性能，将Delaunay三角化过程与谱方法结合起来，提出了一种新的非精确点模式匹配算法。该算法为了缩小非对应点的影响范围，在Delaunay三角化的基础上定义点模式的局部结构，并通过在局部结构层次上应用谱方法找出最相似的局部结构对，然后以此为指导对两个点模式内剩下的点进行匹配。仿真实验结果表明，该算法优于现有的以谱方法为基础的点模式匹配算法。

The point pattern matching algorithm based on the spectral method performs poorly when the two point patterns to be matched are not isomorphic. To improve the matching performance of the spectral method for non-isomorphic point patterns，it is combined with Delaunay triangularization process and a new inexact point pattern matching algorithm is proposed. The algorithm defines the point patterns’ local structures based on Delaunay triangularization to reduce the influenced area of the points that are in one point pattern and have no correspondent in the other. The local structures from the two point pattern are matched with each other using the spectral method. After the most similar local structure pair is found it is used to guide the matching of the remaining points within the two point patterns. Simulation experiments show that the proposed algorithm is superior to the existing point pattern matching algorithms which are based on the spectral method.