基于一种快速搜索策略的图像匹配

基于灰度相关的图像匹配法,因匹配概率高而广泛应用于各个领域,但传统灰度相关算法的搜索策略是遍历性的,匹配速度较慢。为提高图像匹配速度,提出一种全局并行爬山搜索策略,实现了非遍历性搜索,并能快速找到最优匹配点,并引入了一个搜索路经表对已搜索过的点作标记,以防止对某些点的重复搜索。实验结果表明了该算法的图像匹配具有快速性和较高的准确性。

Image matching based on a fast searching strategy

Image matching based on grey cross-correlation,has been widely applied to various field because of its high matching probability.But the searching strategy of conventional grey cross-correlation algorithm is ergodic,the speed of matching is slow.To improve the speed of image matching,a global and parallel hillclimbing searching strategy are presented,which realized non-ergodic searching and can be used to find the best matching point very quickly,also introduced a searching path-table to marker the point which had been searched.Experiment show that this approach has high speed and accuracy in image matching.