颜色聚类

这是一个按照图片颜色深浅的聚类算法

 1 function [ result ] = my_kcluster_random( imgAddress )
 2 %UNTITLED Summary of this function goes here
 3 %   Detailed explanation goes here
 4 img_original = imread(imgAddress);                %读入图像
 5 img_gray = rgb2gray(img_original);
 6 [m, n] = size(img_gray);
 7 temp = zeros(m*n,1);
 8 temp_one = zeros(m*n,1);
 9 temp_two = zeros(m*n,1);
10 % 将图像进行RGB——3通道分解
11 R = reshape(img_original(:, :, 1), m*n, 1);    % 将RGB分量各转为kmeans使用的数据格式n行，一样一样本
12 G = reshape(img_original(:, :, 2), m*n, 1);
13 B = reshape(img_original(:, :, 3), m*n, 1);
14 dR = double(R);
15 dG = double(G);
16 dB = double(B);
17 x1 = 1;
18 temp(x1) = 1;
19 temp_one(1) = x1;
20 mn = m * n;
21 max = 0.0;
22 i = 1;
23 for k = 1 : mn                               %选取第二个类的初始点
24     dist = sqrt((dR(x1)-dR(k))^2 + (dG(x1)-dG(k))^2 + (dB(x1)-dB(k))^2);
25     if(dist > max)
26         max = dist;
27         i = k;
28     end
29 end
30 x2 = i;
31 temp(x2) = 2;
32 temp_two(1) = x2;
33 one = 1;
34 two = 1;
35 dist_cluster_one = 65535;
36 dist_cluster_two = 65535;
37 for k = 1 : mn                                         %聚类
38     if(temp(k) == 0 && x1 > 0 && x2 > 0)
39          dist_cluster_one = sqrt((dR(x1)-dR(k))^2 + (dG(x1)-dG(k))^2 + (dB(x1)-dB(k))^2);
40          dist_cluster_two = sqrt((dR(x2)-dR(k))^2 + (dG(x2)-dG(k))^2 + (dB(x2)-dB(k))^2);
41     end
42     if(dist_cluster_one < dist_cluster_two)
43             temp(k) = 1;
44             one = one + 1;
45             temp_one(one) = k;
46     else
47             temp(k) = 2;
48             two = two + 1;
49             temp_two(two) = k;
50     end
51     x1 = rand(1,1) * one;
52     x1 = int8(x1) + 1;
53     x1 = temp_one(x1);
54     x2 = rand(1,1) * two;
55     x2 = int8(x2) + 1;
56     x2 = temp_two(x2);
57 end
58 for k = 1 : mn                                 %将其中一类用红色点显示
59     if(temp(k) == 1)
60         R(k) = 0;
61         G(k) = 0;
62         B(k) = 0;
63     end
64 end
65
66 for k = 1 : mn                                 %将其中一类用红色点显示
67     if(temp(k) == 2)
68         R(k) = 255;
69         G(k) = 255;
70         B(k) = 255;
71     end
72 end
73
74 dat = [R, G, B];
75 result = reshape(dat,m,n,3);
76
77 end

对文件夹中的图片处理

 1 function [ output_args ] = ccluster_compare(  )
 2 %UNTITLED5 Summary of this function goes here
 3 %   Detailed explanation goes here
 4 pictures1 = dir(‘C:\Users\george\Desktop\obj1\*.png‘);
 5 pictures2 = dir(‘C:\Users\george\Desktop\obj2\*.png‘);
 6 [rp cp] = size(pictures1);
 7 for i = 1:rp
 8     img = strcat(‘C:\Users\george\Desktop\obj1\‘,pictures1(i).name);
 9     result = my_cluster(img);
10     img = strcat(‘C:\Users\george\Desktop\obj1\1obj\‘,pictures1(i).name);
11     saveas(result,img);
12     img = strcat(‘C:\Users\george\Desktop\obj2\‘,pictures2(i).name);
13     result = my_cluster(img);
14     img = strcat(‘C:\Users\george\Desktop\obj2\2obj\‘,pictures1(i).name);
15     saveas(result,img);
16 end
17 end

颜色聚类