作业6

说明：  主成分分析方法PCA与灰度共生矩阵GLCM 主成分分析方法是一种使用最广泛的数据降维算法。 灰度共生矩阵是一种描述图像局部区域或整体区域的某像素与相邻像素或一定距离内的像素的灰度关系的矩阵。即求灰度图像中某种形状的像素对，在全图中出现的次数。(PCA and Gray Co-occurrence Matrix GLCM The principal component analysis method is one of the most widely used data reduction algorithms. The gray level co-occurrence matrix is a matrix describing the gray level relationship between a pixel in a local area or an entire area of an image and neighboring pixels or pixels within a certain distance. That is to find the number of times a pixel pair of a certain shape appears in the whole image in a grayscale image.)