Hausdorff距离和量子粒子群的二维图像匹配

2-D image matching based on Hausdorff distance and quantum particle swarm optimization

提出了一种基于Hausdorff距离和量子粒子群算法的二维图像匹配算法。为了实现二维图像的搜索,首先利用Canny算子提取图像的边缘,再利用Hausdorff距离作为图像搜索的目标函数,然后引入了带量子行为的粒子群的优化算法来求解搜索所需的空间变化参数,实验结果表明,带量子行为的粒子群的优化算法(QPSO)能够迅速地在全局范围内找到最优解,因此应用于二维图像搜索是可行的。

A two-dimensional image matching method based on the Hausdorff distance and Quantum Particle Swarm Optimization（QPSO） is presented.First,edges are extracted from the original images by the Canny edge detector.Then,a similarity function based on the Hausdorff distance is constructed.Finally,the（QPSO） is adopted to optimize the similarity function.Experiments show that the proposed method is able to locate the object of interest globally and efficiently.