基于k-means的图像分割MATLAB程序

close all;
clear;
I_rgb = imread('color-cam4-f0.bmp'); %读取文件数据
figure(1);
subplot(1,2,1);
imshow(I_rgb); %显示原图
title('原始图像');

%将彩色图像从RGB转化到lab彩色空间

C = makecform('srgb2lab'); %设置转换格式
I_lab = applycform(I_rgb, C);

%进行K-mean聚类将图像分割成3个区域
ab = double(I_lab(:,:,2:3)); %取出lab空间的a分量和b分量
nrows = size(ab,1);
ncols = size(ab,2);
ab = reshape(ab,nrows*ncols,2);

nColors = 4; %分割的区域个数为

[cluster_idx cluster_center] = kmeans(ab,nColors,'distance','sqEuclidean','Replicates',100); %重复聚类3次
pixel_labels = reshape(cluster_idx,nrows,ncols);
figure(1);
subplot(1,2,2);
imshow(pixel_labels,[]), title('聚类结果');

%显示分割后的各个区域
segmented_images = cell(1,nColors);
rgb_label = repmat(pixel_labels,[1 1 3]);

for k = 1:nColors
color = I_rgb;
color(rgb_label ~= k) = 0;
segmented_images{k} = color;
end
for i=1:nColors
figure(2),subplot(1,nColors,i);imshow(segmented_images{i}), title('分割结果');
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