Question

我正在学习如何使用kmean聚类来分割颜色，就像matlab 2015a中的示例一样。但每次运行代码时，我想要的颜色都在不同的簇中。例如，对于第一次运行，它将显示黄色在群集1中，蓝色在群集2中。当我再次运行它时，它们将切换到不同的群集。即使我一次又一次地运行，如何使黄色和蓝色在特定的簇中？请帮我。提前致谢

这是我使用的代码：

[FileName,PathName] = uigetfile('*.jpg','Select the MATLAB code file');

he1= imread(FileName);
cform = makecform('srgb2lab');
lab_he = applycform(he1,cform);
figure (2)
imshow (lab_he)


ab = double(lab_he(:,:,2:3));
nrows = size(ab,1);
ncols = size(ab,2);
ab = reshape(ab,nrows*ncols,2);

nColors = 3;
% repeat the clustering 3 times to avoid local minima
[cluster_idx, cluster_center] = kmeans(ab,nColors,'distance','sqEuclidean',           ...
                                  'Replicates',3);



pixel_labels = reshape(cluster_idx,nrows,ncols);
figure (3)
imshow(pixel_labels,[]), title('image labeled by cluster index');

segmented_images = cell(1,3);
rgb_label = repmat(pixel_labels,[1 1 3]);

for k = 1:nColors
    color = he1;
    color(rgb_label ~= k) = 0;
    segmented_images{k} = color;
end
%%
figure (4)
imshow(segmented_images{1}), title('objects in cluster 1');

%% 
figure (5)
imshow(segmented_images{2}), title('objects in cluster 2');

%%
figure (6)
imshow(segmented_images{3}), title('objects in cluster 3');
%%
a = im2bw (segmented_images{2},0.05);
figure (7)
imshow (a);

b = im2bw (segmented_images{3},0.05);
figure (8)
imshow (b);

在我的情况下，黄色区域应该在第2组中，蓝色区域应该在第3组中。请告诉我该怎么做

Answer 1

kmeans的第一个输出位于群集的索引中，而不是颜色。您所指的颜色是MATLAB在您可视化时显示的颜色。

使用kmeans，从输入数据中随机选择初始聚类中心。因此，顺序是随机的。因此，每次调用算法时，哪个群集索引分配给像素都会有所不同，但群集中的像素应放在同一群集中，并且彼此具有相同的群集索引连续的电话。

如果您想要与每个群集对应的实际颜色，则需要使用kmeans ind2rgb（群集质心）将群集索引映射到颜色。您可以使用pixel_labels = ind2rgb(cluster_idx, cluster_center); imshow(pixel_labels)轻松完成此操作。

cluster_center

如果您只是希望在连续调用后集群索引值保持不变，则可以使用[cluster_idx, cluster_center] = kmeans(ab, nColors); [~, ind] = sortrows(cluster_center); pixel_labels = reshape(cluster_idx, nrows, ncols); for k = 1:numel(ind) pixel_labels(cluster_idx == k) = ind(k); end来确保一致的索引分配

%// Define yellow
yellow = [1 1 0];

%// Define blue
blue = [0 0 1];

%// Find the centroid closest to yellow
[~, yellowind] = min(sum(bsxfun(@minus, cluster_center, yellow).^2, 2));

%// Find the one closest to blue
[~, blueind] = min(sum(bsxfun(@minus, cluster_center, blue).^2, 2));

%// Now assign them to clusters with yellow as 2 and blue as 3
segmented_images{1} = cluster_idx == setdiff(1:3, [yellowind, blueind]);
segmented_images{2} = cluster_idx == yellowind;
segmented_images{3} = cluster_idx == blueind;

如果您希望特定颜色位于特定群集中，则可以修改此项。

 git clone path/to/local/repo c/tempRepo -b development

为什么kmean颜色分割每次都显示不同的颜色？

1 个答案: