对用于图像特征定位的标准互相关算子灰度无关特性展开了研究.由于在显微视觉中的大多数图像灰阶较低，接近于三值甚至二值图像；可籍此灰度无关特性对模板匹配的算法进行优化.实验结果表明，标准互相关的灰度无关特性可以在实际中指导设计模板图像，降低相关运算计算速度，以及指导改善照明条件.

A characteristic that Normalized Cross Correlation Operating (NCCO) results independent of image gray levels in pattern matching for image feature positioning was presented.In the field of microscopic vision research,the majority of images can be approximated to an image with three gray levels,or even binary image.So with this attractive feature,a method of improved pattern matching algorithms was presented.Experimental results show that the characteristic of gray level independence can give guidance to designing template images,reducing time consumption of calculations,and improving illuminating conditions.