Posted By

engrhassan2k13 on 07/07/15


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MatlabImage-processingMachine-Learning


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Automatic Thresholding with Expectation Maximization Algorithm in Matlab


 / Published in: MatLab
 

This code uses the Expectation Maximization algorithm for automatically thresholding an image.

  1. %read image
  2. img1 = rgb2gray(imread('dino.jpg'));%use your image here
  3. imshow(img1);
  4.  
  5. %parameter initialization for EM-Algo
  6. temp =[];
  7. phi1 = 0.5;
  8. phi2 = 0.5;
  9. u1 = 0;
  10. u2 = 50;
  11. sig1 = 2;
  12. sig2 = 3;
  13. tempimg1 = reshape(img1,1,numel(img1));
  14. tempimg1 = double(tempimg1);
  15. img = double (img1);
  16.  
  17.  
  18. for k = 1 : 3
  19.  
  20. for i = 1 : numel(img1)
  21. %Expectation Step
  22. prob1 = -0.9181-reallog(sig1)-( (( img(i)- u1 )^2)/(2*(sig1^2)) );
  23. prob2 = -0.9181-reallog(sig2)-( (( img(i)- u2 )^2)/(2*(sig2^2)) );
  24.  
  25. probc1 = ( prob1*phi1 ) / ( (prob1*phi1)+ (prob2*phi2) );
  26. probc2 = ( prob2*phi2 )/( (prob1*phi1) + (prob2*phi2) );
  27.  
  28. temp = [temp ; probc1 probc2];
  29.  
  30. end
  31. %Maximization Step
  32.  
  33. phi1 = ( sum(temp(:,1)) )*(1/numel(img));
  34. phi2 = (sum(temp(:,2)))*(1/numel(img));
  35.  
  36.  
  37. u1 = ( sum((temp(:,1)').*tempimg1) )/( sum(temp(:,1)) );
  38. u2 = ( sum((temp(:,2)').*tempimg1) )/( sum(temp(:,2)) );
  39.  
  40. var1 = ( sum( ( (tempimg1 - u1).^2 ).*( temp(:,1)' ) ) ) / ( sum(temp(:,1)) );
  41. sig1 = sqrt(var1);
  42. var2 = ( sum( ( (tempimg1 - u2).^2 ).*( temp(:,2)' ) ) ) / ( sum(temp(:,2)) );
  43. sig2 = sqrt(var2);
  44.  
  45. temp = [];
  46.  
  47. end
  48.  
  49. %Thresholding
  50. thresh = ((u2 + u1)/2);
  51.  
  52. for m = 1 : numel(img1)
  53. if img1(m) > thresh
  54. img1(m) = 255;
  55. else
  56. img1(m) = 0;
  57. end
  58. end
  59.  
  60. imshow(img1);

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