实现K-means算法，高斯随机分布抽取数据 利用k-means算法实现分类-Implement K-means algorithm to extract the data using Gaussian random distribution of k-means classification algorithm

基于opencv实现的c++版高斯判别分类，随机生成两类满足正态分布的训练样本点，利用高斯判别分析进行分类-Based on c++ version of the opencv, we realized gaussian discriminant classification by randomly generating two classes meet normal distribution of the training sample points, and used gaussian di

加入随机噪声，高斯白噪声等 后期去噪处理。-Added random noise, post-processing de-noising.