How to fit Gaussian mixture models on image histogram?

Question

Mohamed Hassan 2022-6-22

0
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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/1745350-how-to-fit-gaussian-mixture-models-on-image-histogram

回答： Akshat 2023-9-1

Hello all,

I am writing a code to seperate clusters of an image. I did this part. However, I want to show the GMM on the image Histogram. Here the code that I used:

% Read Image
I = im2double(imread('test.tif'));
mask = I > 0 & I < 65536; %remove background
I1 = I(mask);
data = I1(:);
% Fit a gaussian mixture model
n_components = 4;
obj = fitgmdist(data,n_components);
idx = cluster(obj,data);
cluster1 = data(idx == 1,:);
cluster2 = data(idx == 2,:);
cluster3 = data(idx == 3,:);
cluster4 = data(idx == 4,:);
% Display Histogram
histogram(cluster1,0:.01:1); hold on;
histogram(cluster2,0:.01:1); hold on;
histogram(cluster3,0:.01:1); hold on;
histogram(cluster4,0:.01:1);

I would also like to show each cluster as a seperate Gaussian curve.

Thanks,

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Answer 1

Akshat 2023-9-1

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此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/1745350-how-to-fit-gaussian-mixture-models-on-image-histogram#answer_1299196

在 MATLAB Online 中打开

image_gen.m

Hi Mohamed,

I understand that you would like to plot a depiction of the GMM over the image histogram you are generating in the code you mentioned. I assume that the PDF (Probability Density Function) is a good depiction of the GMM.

As you did not provide any image for the question, I generated an image using the code attached as image_gen.m. Kindly refer it in case you want to know what the image looks like.

Below is the modified code:

% Read Image 
I = im2double(imread('test.tif')); 
 
mask = I > 0 & I < 65536; % Remove background 
I1 = I(mask); 
data = I1(:); 
 
% Fit a Gaussian mixture model 
n_components = 4; 
obj = fitgmdist(data, n_components); 
idx = cluster(obj, data); 
cluster1 = data(idx == 1, :); 
cluster2 = data(idx == 2, :); 
cluster3 = data(idx == 3, :); 
cluster4 = data(idx == 4, :); 
 
% Display Histogram 
 
histogram(cluster1, 0:.01:1); hold on; 
histogram(cluster2, 0:.01:1); hold on; 
histogram(cluster3, 0:.01:1); hold on; 
histogram(cluster4, 0:.01:1); hold off; 
 
% Plot GMM PDFs on the histogram 
x = linspace(0, 1, 101); % Values for x-axis 
x = x';  
pdf1 = pdf(obj, x); % GMM PDF for cluster 1 
pdf2 = pdf(obj, x); % GMM PDF for cluster 2 
pdf3 = pdf(obj, x); % GMM PDF for cluster 3 
pdf4 = pdf(obj, x); % GMM PDF for cluster 4 
 
binEdges = 0:.01:1; 
figure; 
histogram(cluster1, binEdges); hold on; 
plot(x, pdf1 * numel(cluster1) * diff(binEdges(1:2)), 'r', 'LineWidth', 2); 
histogram(cluster2, binEdges); hold on; 
plot(x, pdf2 * numel(cluster2) * diff(binEdges(1:2)), 'g', 'LineWidth', 2); 
histogram(cluster3, binEdges); hold on; 
plot(x, pdf3 * numel(cluster3) * diff(binEdges(1:2)), 'b', 'LineWidth', 2); 
histogram(cluster4, binEdges); hold on; 
plot(x, pdf4 * numel(cluster4) * diff(binEdges(1:2)), 'm', 'LineWidth', 2); 
hold off; 
% Set plot labels and title 
xlabel('Pixel Value'); 
ylabel('Frequency'); 
title('Image Histogram with GMM PDFs'); 
legend('Cluster 1', 'Cluster 1 PDF', 'Cluster 2', 'Cluster 2 PDF', 'Cluster 3', 'Cluster 3 PDF', 'Cluster 4', 'Cluster 4 PDF'); 
 