如何在matlab中基于颜色精确地排序聚类 [英] How to accurately order the clusters based on color in matlab

问题描述

我有一张叶子的图像，主要有三种颜色的黑色背景，绿色的叶子和棕色的病斑。
这是图像

当我集群它第一次，我得到棕色斑点在集群1，绿色部分在集群2，黑色区域在集群3（例如）。

，我得到群集1中的绿色部分，群集2中的褐色斑点，群集3中的黑色区域（例如）。 b

当我第三次集群时，集群的顺序会再次不同。

代码，使得棕色斑点出现在群集1，绿色部分群集2和黑色的群集3.群集的顺序应该是相同的，即使我群集多次。有人可以帮助我的代码吗？我使用Matlab2009a。

 <$ c 
 $ c> function segmented_img = leaf_segmentation（original_img，nclusters）
 
 original_img = im2double（original_img）; 
 G = fspecial（'gaussian'，[200 250]，1）; 
 smoothed_img = imfilter（original_img，G，'same'）; 
 
 conversionform = makecform（'srgb2lab'）; 
 lab_img = applycform（smoothed_img，conversionform）; 
 
 ab_img = double（lab_img（：，：，2：3））; 
 nrows = size（ab_img，1）; 
 ncols = size（ab_img，2）; 
 ab_img = reshape（ab_img，nrows * ncols，2）; 
 
 cluster_idx = 
 kmeans（ab_img，nclusters，'distance'，'sqEuclidean'，'Replicates'，3）; 
 cluster_img = reshape（cluster_idx，nrows，ncols）; 
 segmented_img = cell（1，nclusters）; 
 for k = 1：nclusters 
 segmented_img {k} = bsxfun（@times，original_img，cluster_img == k）; 
 end 
 
 
 end 
 
 
 segmented = leaf_segmentation（imread（'input image'），3）; 
 
 figure，imshow（segmented {1}），title（'Cluster 1'）; 
 figure，imshow（segmented {2}），title（'Cluster 2'）; 
 figure，imshow（segmented {3}），title（'Cluster 3'） 
  

解决方案

只要在聚类后检查颜色！

这样做的一种方法是将质心颜色空间转换为HSV，并检查H和V的值.H会给你颜色（例如，它的绿色约为120.0度）和V将给你ligth，所以如果V是0，那么无论什么H，它是黑色的簇。

这对于程序来说应该是微不足道的，但不要犹豫要问任何问题。

I have an image of leaf that has mostly three colors black background, green leaf and brown diseased spots. Here is the image

When I cluster it first time, I get brown spots in cluster 1, green portion in cluster 2, black region in cluster 3(for example).

When I cluster it second time, I get green portion in cluster 1,brown spots in cluster 2, black region in cluster 3(for example). b

When I cluster it third time the order of clusters are different again.

I want to change the code such that the brown spots appear in cluster 1, green portion in cluster 2 and black in cluster 3. The order of clusters should be same even if I cluster many times.Could someone please help me with the code? I am using Matlab2009a. This question is about ordering clusters

Here is what is being done so far

function segmented_img = leaf_segmentation( original_img, nclusters )

original_img = im2double(original_img);
G=fspecial('gaussian',[200 250],1);
smoothed_img =imfilter(original_img,G,'same');

conversionform = makecform('srgb2lab');
lab_img = applycform(smoothed_img,conversionform);

ab_img = double(lab_img(:,:,2:3));
nrows = size(ab_img,1);
ncols = size(ab_img,2);
ab_img = reshape(ab_img,nrows*ncols,2);

cluster_idx =   
kmeans(ab_img,nclusters,'distance','sqEuclidean','Replicates',3);
cluster_img = reshape(cluster_idx,nrows,ncols);
segmented_img = cell(1,nclusters);
for k = 1:nclusters
   segmented_img{k} = bsxfun( @times, original_img, cluster_img == k );
end


end


segmented = leaf_segmentation( imread('input image'), 3 );

figure,imshow(segmented{1}), title('Cluster 1');
figure, imshow(segmented{2}), title('Cluster 2');
figure, imshow(segmented{3}), title('Cluster 3');

解决方案

Just check the colors after the clustering!

One way of doing this is transforming the centroids color space to HSV and checking the values oh H and V. H will give you the color (for example, around 120.0 degrees its green) and V will give you the "ligth", so if V is 0 then whatever H is, it is the black cluster.

This should be trivial to program, but dont hesitate to ask any questions about it.

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