人们在对图像灰度值做统计分析时，大都采用正态分布来分析，但从大量的实验中发现，其大部分不是完全服从正态分布，有的甚至相差很远，这样就有必要用更好的分布来拟合图像灰度。通过对物体的颜色、光强进行分析发现，人们看到的物体颜色是多种环境——环境光强、漫反射、镜面反射等等共同作用的结果。这样如果单纯地用正态分布来分析就会出现较大的偏差，那么也就不能很好地拟合图像灰度分布曲线，因此这里提出了用χ^2分布来拟合图像灰度的分布曲线，实验结果表明，通过χ^2分布可以得到更好的分割效果。

When the images are assayed by the statistics, all most of images are assayed by normal distribution. But in large numbers of experimentation most of the images can' t submit to normal distribution perfectly. Some simulated result is different from the actual images. So it is necessary to assay the images by better distribution. When the color and the intensity of images are assayed, it can be found that the color of the object what people have seen is impacted by plenty of environments, such as the intensity light of the environment、diffused reflection and mirror reflection and so on. Then an object's color isn't symmetrical distribution. So it will turn up larger warp and can't simulate the distribution curve of the image greatly, if the image is assayed by normal distribution. So here the method that simulate curve byχ2distribution is proposed.χ2distribution is one of the methods that are common used in statistics. Sometimesχ2distribution can replace normal distribution. Soχ2 distribution is proposed. And better result of the segmentation has been gotten in the experimentation byχ2distribution.