CODEWITHSUNDEEP
matlabrandom2dgaussian
user2137591
user2137591

Reputation: 1

creatig random gaussians on an image

I am trying to create some Gaussian distributions and put them on an image. The Gaussians have randomly created parameter (amplitude, position and standard deviation). First I put the parameters into vectors or matrices, then I am using ngrid() function to get a 2d space to create the Gaussians, however i get an error (since possibly mathematical operations with ngrid values is not trivial...). The error is:

     ??? Error using ==> minus
Integers can only be combined
with integers of the same class,
or scalar doubles.
Error in ==> ss_gauss_fit at 23
  gauss = amp(i)*
  exp(-((x-xc).^2 +
  (y-yc).^2)./(2*std(i)));

the code is here:

clear all;
image = uint8(zeros([300 300]));
imsize=size(image);

noOfGauss=10;
maxAmpGauss=160;
stdMax=15;
stdMin=3;

for i=1:noOfGauss
    posn(:,:,i)=[  uint8(imsize(1)*rand())   uint8(imsize(2)*rand())  ];
    std(i)=stdMin+uint8((stdMax-stdMin)*rand());
    amp(i)= uint8(rand()* maxAmpGauss);
end

% draw the gaussians on blank image
for i=1:noOfGauss
    [x,y] = ndgrid(1:imsize(1), 1:imsize(2));
    xc = posn(1,1,i);
    yc = posn(1,2,i);
    gauss = amp(i)* exp(-((x-xc).^2 + (y-yc).^2)./(2*std(i)));

    image = image + gauss;
end

Please tell me how fix this, plot 2d Gaussians with parameter vectors... Thanks in advance

Upvotes: 0

Views: 263

Answers (1)

Andrew Mao
Andrew Mao

Reputation: 36940

Apart from the craziness about "drawing on an image", which I don't really understand, I think you are trying to add up a bunch of separate gaussian distributions on a grid. Here's what I did with your code. Note that your bivariate gaussians are not normalized properly and you were using the variance and not standard deviation before. I fixed the latter; however, I didn't bother with the normalization because you are multiplying each by an amplitude value anyway.

clear all;
xmax = 50;
ymax = 50;

noOfGauss=10;
maxAmpGauss=160;
stdMax=10;
stdMin=3;

posn = zeros(noOfGauss, 2);
std = zeros(noOfGauss, 1);
amp = zeros(noOfGauss, 1);

for i=1:noOfGauss
    posn(i,:)=[ xmax*rand()  ymax*rand() ];
    std(i)=stdMin+(stdMax-stdMin)*rand();
    amp(i)= rand()* maxAmpGauss;
end

% draw the gaussians
[x,y] = ndgrid(1:xmax, 1:ymax);
z = zeros(xmax, ymax);

for i=1:noOfGauss    
    xc = posn(i,1);
    yc = posn(i,2);    
    z = z + amp(i)* exp(-((x-xc).^2 + (y-yc).^2)./(2*std(i)^2));
end 

surf(x, y, z);

Random output:

enter image description here

Upvotes: 1

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