grayscale image clustering, show ouput image from matrix

1 view (last 30 days)
Hello, I want a grayscale image clustering according intersity colors from 0-255.
my code:
I = imread('obraz1.png');
I=rgb2gray(I);
imshow(I);
title('Grayscale image','FontSize',16,'Color','k');
I=double(I);
maxi=max(I(:));
I=I./maxi;
[m n]=size(I);
P = [];
for i=1:m
for j=1:n
if I(i,j)<1 %%All except white
P=[P; i j ];
end
end
end
size(P);
MON=P;
[IDX]= kmeans(MON,3,'emptyaction','singleton')
how do i display image after clustering ?

Answers (1)

Image Analyst
Image Analyst on 27 Apr 2014
I'd guess create a classified image by going down IDX and setting the value of the classified image to either 1, 2, or 3 for each pixel, depending on what class it is.
  3 Comments
Image Analyst
Image Analyst on 28 Apr 2014
I don't have the Statistics Toolbox so I can't be sure but don't you think it would go like this
classifiedImage = zeros(size(I), 'int32');
for p = 1 : length(IDX)
row = P(p, 1);
column = P(p, 2);
% Set this pixel of the classified image
% to the class it identified for that pixel.
classifiedImage(row, column) = IDX(p);
end
I've never used kmeans since I don't have the toolbox but I just read the documentation for a minute and that's what I came up with. It seemed really really obvious to me, though it's probably not right since you worked on it for a whole week, so what I came up with in less than a minute can't be right. But for what it's worth, that's my best guess.
Tomas
Tomas on 28 Apr 2014
Edited: Tomas on 28 Apr 2014
Thank you it works. it is logically correct final image compared to the input image ?
Thank you for your feedback.
input image
output image

Sign in to comment.

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!