摘要
研究了面向微操作的显微视觉系统自动聚焦评价函数和聚焦控制策略;首先,分析显微图像特点并做预处理;接着引入像素相关性指标,并结合梯度函数形成一种新的图形清晰度评价函数,改善了函数的灵敏度和抗噪性;最后对传统爬山算法进行改进,在粗调阶段以大步长搜索并用曲线拟合的方法快速定位到峰值点附近,精调阶段以小步长搜索到评价函数值下降点即可准确定位到焦平面,该算法避免了复杂的阈值设定问题,与传统爬山法相比,在一定程度上提高了聚焦速度,并大幅提高了聚焦成功率。
This paper has done the research to the micro vision auto focusing evaluation function and focusing control strategy for micro operation.First of all,the characteristics of microscopic images are analyzed and pre-processed.Then the pixel correlation index is introduced and a new grayscale evaluation function is formed by combining with the gradient function to improve the sensitivity and noise immunity of the function.Finally improved the traditional hill-climbing algorithm.In the coarse tuning stage,a large step size is searched and the curve fitting method is used to quickly locate the near actual extreme value point.In the stage of fine tuning,a small step size is used to locate the focal plane accurately.The algorithm avoids the complex threshold setting problem.Compared with the traditional hill-climbing method,the focusing speed is improved to a certain extent,and the success rate of focusing is greatly improved.
作者
吴云飞
陈国良
徐扬
Wu Yunfei;Chen Guoliang;Xu Yang(Institute of Electrical and Mechanical Engineering,Wuhan University of Technology,Wuhan 430070,China)
出处
《计算机测量与控制》
2018年第10期174-177,共4页
Computer Measurement &Control
基金
国家自然科学基金项目(61672396)
关键词
显微视觉
聚焦评价函数
相关性加权
曲线拟合
micro vision
focus evaluation function
correlation weighting
curve fitting