for loop, assign variable
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Hi, I am trying to assign distance between each pixel and picked point on mri to variable ed in for loop. However all elements are same. I dont understand the reason. Thank you...
clc;
clear all;
a=imread('tumor.jpeg');
b=imresize(a,3);
c=im2bw(b);
imshow(c);
d=zeros(size(c));
%150,210
[ptx,pty] = ginput(1);
newdata=[ptx, pty];
n=25;
%[count,x] = imhist(c);
[rows, columns]=size(c);
for i=1:rows
for j=1:columns
%calc and store sorted euclidean distances with corresponding indices
ed(i)=sqrt(sum((newdata-c(i,j)).^2));
euc=ed';
end
end
1 Comment
Bjorn Gustavsson
on 12 Jul 2019
Your newdata are a selected point in the image, while c is the intensity (grayscale) of your pixels. This looks like a bug to me. I guess that you either want the length between th image pixels and your selected pixel, that would be norm(newdata-[j,i]), or the grayscale difference between the pixels and the pixel closest to newdata, that would be c(round(newdata(2)),round(newdata(1)))-c(i,j).
Answers (3)
KSSV
on 12 Jul 2019
Edited: KSSV
on 12 Jul 2019
You should initiliaze ed before the loop.
for i=1:rows
for j=1:columns
%calc and store sorted euclidean distances with corresponding indices
ed(i,j)=sqrt(sum((newdata-c(i,j)).^2));
end
end
Loop is not required here.
ed=sqrt((newdata(1)-c).^2+(newdata(2)-c).^2);
3 Comments
KSSV
on 12 Jul 2019
YOur c is a matrix......a point subtracted from matrix..will give you a matrix. How it will be of only size 528?
KSSV
on 12 Jul 2019
Try:
a=imread('image.jpeg');
b=imresize(a,3);
c=im2bw(b);
imshow(c);
d=zeros(size(c));
%150,210
[ptx,pty] = ginput(1);
newdata=[ptx, pty];
n=25;
%[count,x] = imhist(c);
[nx,ny] = size(c) ;
[X,Y] = meshgrid(1:nx,1:ny) ;
ed=sqrt((newdata(1)-X).^2+(newdata(2)-Y).^2);
Alex Mcaulley
on 12 Jul 2019
Edited: Alex Mcaulley
on 12 Jul 2019
As Bjorn Gustavsson said your code make no sense. To calculate distances you have to use the coordinates of each pixel, not mixing coordinates and intensity values. One option without loop:
a = imread('tumor.jpeg');
b = imresize(a,3);
c = im2bw(b);
imshow(c);
d = zeros(size(c));
%150,210
[ptx,pty] = ginput(1);
newdata = [ptx, pty];
n = 25;
%[count,x] = imhist(c);
[rows, columns] = size(c);
crows = repmat((1:rows)',1,columns);
ccolumns = repmat(1:columns,rows,1);
euc = sqrt((newdata(1) - crows).^2 + (newdata(2) - ccolumns).^2)
2 Comments
KSSV
on 12 Jul 2019
crows = repmat((1:rows)',1,columns);
ccolumns = repmat(1:columns,rows,1);
The above is not good. Use meshgrid
Alex Mcaulley
on 12 Jul 2019
Edited: Alex Mcaulley
on 12 Jul 2019
Why is not good? The code works and the execution time is similar than using meshgrid (In fact, my code results in a slightly better performance in my computer).
%5 different executions
nx = 512;
ny = 512;
timeit(@() meshgrid(1:nx,1:ny))
timeit(@() repmat((1:nx)',1,ny)) + timeit(@() repmat(1:ny,nx,1))
%1st
ans =
0.0013
ans =
0.0011
%2nd
ans =
0.0015
ans =
0.0011
%3rd
ans =
0.0014
ans =
0.0012
%4th
ans =
0.0014
ans =
0.0012
%5th
ans =
0.0013
ans =
0.0013
Ahsen Feyza Dogan
on 12 Jul 2019
1 Comment
Bjorn Gustavsson
on 12 Jul 2019
Yeah, about that. You have one selected point, lets call that one r_slected and an image, lets call that one Img. Now, from each image pixel you want the distance to r_selected. You get that with KSSV's second suggestion, or Alex's, lets repeat it here:
[ny,nx] = size(Img);
[X,Y] = meshgrid(1:nx,1:ny);
l2slected_point = sqrt((r_selected(1)-X).^2+(r_selected(2)-Y).^2);
That will make l2selected_point a double array of size 528 x 528 (or whatever size your image has), which is your 278784 distances - but you will have them in an order that is sensibly arranged to be of the same size as your image, which will be crucial for further use.
Try this code and before doing anything more display the result:
imagesc(l2selected_point),colorbar
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