图像测量中自动调焦函数的实验研究与分析

给出了几种常用图像测量中自动调焦算法的对比分析,并分别在不同照明方式和不同背景条件下对主要的调焦函数特性参数进行测试,得到了调焦函数的实用性能的客观评价.实验结果表明:在透射照明条件下,灰度梯度类调焦函数特性均较好.其中Variance函数以及灰度变化率和函数具有较大的调焦范围,且近似为线性变化,但是灵敏度较低,因此适于大范围粗调焦;Laplacian函数和Tenengrad函数灵敏度高,稳定性好,但调焦范围小,因此适合于小范围精确调焦.在反射照明条件下,只有Tenengrad函数和Brenner函数仍然保持单峰性,但灵敏度明显下降.当存在较复杂背景时,调焦函数普遍失效.因此在实际测试中,应当优先选择透射光照明,尽可能少用反射照明,而且应尽可能避免背景的干扰.

Experimental research and analysis of automatic focusing function for imaging measurement

Several general automatic focusing functions for imaging measurement are put forward, compared and analyzed in defail. The main parameters of automatic focusing, including sensitivity, consistency, stability and calculating speed, were tested and validated through a series of experiments under different conditions, such as different lighting or different background. The results of experiments show that in the background lighting, the gray functions all have better performance than others, the Variance function and the sum of gray-change function have a large focusing range, good linearity and low sensitivity, so they are propitious to focusing in large range with lower accuracy. The Laplacian and Tenengrad functions both have sharp peak, good sensitivity and small focusing range, which make them applicable to accurate focusing in small range. But in reflection lighting, only the Tenengrad and Brenner functions have fine single peak and low sensitivity. All of these focusing functions will be disabled when the complex backgrounds exist. So, when it comes to practical application, background lighting should be chosen instead of reflection lighting, also interference coming from background should be reduced to minimum level.