摘要
图像匹配是图像处理中的一项重要技术,在许多领域都有广泛的应用。简单地说,它就是找到两幅不同图像之间的空间位置关系。对一种衡量图像之间相似性的推土机距离EMD度量做了介绍,提出了一种基于EMD度量的图像匹配方法。实验结果表明,运用此种技术进行图像匹配相对一些其它的图像匹配方法有更好的效果。
An improved bee evolutionary genetic algorithms (A_BEGA) is proposed. In the algorithms, the best chromosome called queen among the current population is crossovered with drones selected according to a certain crossover probability, which enhances the exploitation of searching global optimum. At the same time, a local search is adopted to randomly produce more parents around the secondary best chromosome, so as to escape the premature and increase the exploration ability. Finally, the experimental results prove that the proposed algorithm is actually a great improvement of genetic algorithms in solution precision and convergence speed.
出处
《计算机工程与设计》
CSCD
北大核心
2008年第11期2863-2867,共5页
Computer Engineering and Design
基金
国家自然科学基金项目(60573066)
广东声自然科学基金项目(5003346)
教育部留学回国人员科研启动基金项目(教外司留[2006]331号).
关键词
图像匹配
相似性度量
推土机距离
特征点
小波变换
bee evolutionary genetic algorithms
parental select operator
local search
convergence
diversity