摘要
综述了显微视觉系统中常用的自动调焦算法,并分别在不同的照明方式和不同的图像内容条件下对其调焦函数特性进行测试,得到了调焦评价函数优劣的客观评价。实验结果表明:梯度平方函数、Tenegrad函数、Laplacian函数灵敏度高,稳定性好,适于小范围精细调焦;Variance函数、熵函数灵敏度低,但调焦范围大,适用于粗调焦;透射照明通常比反射照明有更好的调焦曲线;高频信息丰富的图像宜采用梯度平方函数或Tenegrad函数调焦,高频信息不是很丰富的图像宜采用Laplacian函数调焦。
The algorithm of general focusing function is put forward, and a series of experiments is tested. Focusing character with different lighting and different content is validated and analyzed. The experiment result shows that the functions of gradient energy, Tenegrad, and Laplacian possess the stable, highly sensitive characteristic curve. It＇s better to use in small range with high accuracy; the functions of Variance and entropy have a large focusing range, good linearity and low sensitivity, so they are propitious to focus in large range with lower accuracy. So, there has better performance curve in background lighting than in reflection lighting. It＇s appropriate that using the functions of gradient energy or Tenegrad to focus for the image with more high frequency information, and using Laplacian function for the image with slightly high frequency information.
出处
《半导体光电》
EI
CAS
CSCD
北大核心
2006年第2期216-220,共5页
Semiconductor Optoelectronics
基金
黑龙江省科技攻关基金资助项目(GB02A402)
关键词
自动调焦
评价函数
照明
auto-focus
evaluation function
lighting
