grayscale image clustering, show ouput image from matrix
조회 수: 1 (최근 30일)
이전 댓글 표시
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 ?
댓글 수: 2
Manjurekha M.Phil
2018년 3월 12일
i need grayscale image clustering, show ouput image from matrix source code in matlab
Image Analyst
2018년 3월 13일
답변 (1개)
Image Analyst
2014년 4월 27일
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.
댓글 수: 3
Image Analyst
2014년 4월 28일
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.
참고 항목
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!