摘要
针对人工蜂群算法存在的收敛速度较慢,易陷入局部最优解的问题,提出一种改进的人工蜂群优化算法,并应用于数字图像相关的整像素位移搜索中。该算法借助相关度值的变化来动态调整跟随蜂的搜索步长,平衡其全局和局部的搜索能力;侦察蜂利用遗传算法的交叉运算产生新解,改善全局搜索能力。实验结果表明,改进的算法能有效地提高收敛速度,改善整像素位移搜索的性能。
Aiming at the problems of slow convergence speed and easy to fall into local optimal solution, which exist in artificial bee colony algorithms, an improved artificial bee colony optimization algorithm is proposed for the pixel displacement search in digital image correlation. In the algorithm, the search step of the following bee is adjusted dynamically according to the changes of the correlation to balance the capability of global search and local search, and the scout bee employs crossover operation of genetic algorithm to generate new solution for improving the global search capacity. The experimental results show that the improved algorithm can enhance the convergence capability effectively and improve the performance of integer pixel displacement search.
出处
《现代电子技术》
2013年第24期70-72,76,共4页
Modern Electronics Technique
基金
国家"973"计划项目(2010CB315022)
国家自然科学基金(50905022)
工业装备结构分析国家重点实验室专项基金项目(S09104)
中央高校基本科研业务费专项基金资助(DUT12LK21)
关键词
人工蜂群算法
数字图像相关
变形
整像素位移
动态步长
交叉运算
artificial bee colony algorithm
digital image correlation
deformation
pixel displacement
dynamic step
cross- over operarion
