如何在matlab中对灰度图像应用kmeans聚类

Question

skin cancer image 我想在灰度图上应用K均值聚类，代码如下

    im = imread('SSM1_2_orig.jpg');
im = rgb2gray(im);
[idx centroids]=kmeans(double(im(:)),3,'distance','sqEuclidean','Replicates',3);
%imseg = zeros(size(im,1),size(im,2));
%{for i=1:max(idx)
    %imseg(idx==i)=i;
    %end}
segmented_images = cell(1,3);
for k = 1:3
    color = im;
    color(im ~= k) = 0;
    segmented_images{k} = color;
end

figure(),imshow(segmented_images{1});
figure(),imshow(segmented_images{2});
figure(),imshow(segmented_images{3});

但它只给我黑色输出

Answer 1

这是工作代码。备注：

您从未使用聚类的结果，您将原始像素值与 k 进行比较，而不是将聚类后的像素值 idx.

此外，如果您的图像不是 [0-1] 或 [0-255]，请记住使用 imshow(____, [])。

im = imread('https://i.stack.imgur.com/ZYp7r.jpg');
im = rgb2gray(im);
[idx, centroids]=kmeans(double(im(:)),3,'distance','sqEuclidean','Replicates',3);

segmented_images = cell(1,3);
for k = 1:3
    color = zeros(size(im));
    color(idx==k) = im(idx==k);
    segmented_images{k} = color;
end

figure(),imshow(segmented_images{1},[]);
figure(),imshow(segmented_images{2},[]);
figure(),imshow(segmented_images{3},[]);

如何在matlab中对灰度图像应用kmeans聚类

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