Image segmentation post conversion of image to HSV space

So I'm working on image segmentation and I was able to successfully cluster (via kmeans clustering) the components in the image. I was able to "blue" the segmented parts of the image as seen below:

This is the code I came up with for implementation:

MATLAB code:
clear all;close ALL;
A=imread('stopcup.jpg');
%A = rgb2hsv(A); %converting the image to HSV space
subplot(2,3,1),imshow(A), title('original image'); 
title('Original Image');
F = makecform('srgb2lab'); %converting the image to L*a*b color space to quantify visual differences.
F1 = applycform(A,F); 
img = double(F1(:,:,2:3));
R = size(img,1);
C = size(img,2);
img = reshape(img,R*C,2);
colors = 4; 
[cindex, ccenter] = kmeans(img,colors,'distance','sqEuclidean', ...
                                    'Replicates',3); %K means clustering, done 3 times, to group the color regions.                                 
plabels = reshape(cindex,R,C);
subplot(2,3,2),imshow(plabels,[]), title('cluster index');
pause;
img_seg = cell(1,4); %creating four cluster images
rgbl = repmat(plabels,[1 1 3]);
for k = 1:colors
  color = A;
  color(rgbl ~= k) = 0;
  img_seg{k} = color;
end
threshold=20;
for row=1:size(img_seg{1},1)
for col=1:size(img_seg{1},2)
  for rgb=1:size(img_seg{1},3)
        if(img_seg{1}(row,col,rgb)>=threshold)            
           if(rgb==3)
                img_seg{1}(row,col,rgb)=125;
           else
              img_seg{1}(row,col,rgb)=0;
          end
        end
  end
end
end
threshold=20;
for row=1:size(img_seg{2},1)
for col=1:size(img_seg{2},2)
  for rgb=1:size(img_seg{2},3)
        if(img_seg{2}(row,col,rgb)>=threshold)            
           if(rgb==3)
                img_seg{2}(row,col,rgb)=125;
           else
              img_seg{2}(row,col,rgb)=0;
          end
        end
  end
end
end
threshold=20;
for row=1:size(img_seg{3},1)
for col=1:size(img_seg{3},2)
  for rgb=1:size(img_seg{3},3)
        if(img_seg{3}(row,col,rgb)>=threshold)            
           if(rgb==3)
                img_seg{3}(row,col,rgb)=125;
           else
              img_seg{3}(row,col,rgb)=0;
          end
        end
  end
end
end
threshold=20;
for row=1:size(img_seg{4},1)
for col=1:size(img_seg{4},2)
  for rgb=1:size(img_seg{4},3)
        if(img_seg{4}(row,col,rgb)>=threshold)            
           if(rgb==3)
                img_seg{4}(row,col,rgb)=125;
           else
              img_seg{4}(row,col,rgb)=0;
          end
        end
  end
end
end
subplot(2,3,3),imshow(img_seg{1}), title('cluster 1');
pause;
subplot(2,3,4),imshow(img_seg{2}), title('cluster 2');
pause;
subplot(2,3,5),imshow(img_seg{3}), title('cluster 3');
pause;
subplot(2,3,6),imshow(img_seg{4}), title('cluster 4');

I tried implementing the same procedure by converting the image to HSV space

MATLAB code:
clear all;close ALL;
A=imread('stopcup.jpg');
A = rgb2hsv(A); %converting the image to HSV space
imhist(A(:,:,1)),figure, imshow(A(:,:,1));

I know the concept of ranging the threshold values for each of the four colors from the image histogram:

My question is how do I add the respective threshold value ranges in to the mentioned coding (that I used prior to image conversion to HSV) thereby getting the corresponding output? Could someone just highlight the section of my coding, by including threshold range coding for at least one threshold range, where I should add the threshold values please?

Note: A "threshold" of the hue component of pixels must be an interval, because the hue actually wraps around and is best envisioned as a circle. Thus, to segment a blue region, I need to accept only hues around 2/3 (0 = red, 1/3 = green, 2/3 = blue).

Thanks, Shyam

Answer 1

[Image Analyst]

Run the color thresholder app on the Apps tab and have it generate code for you.

[Image Analyst]

h = A(:,:,1);
hueMask = h > 0.2 & h < 0.8; % or whatever...

[Shyam]

Thanks for a prompt reply Image Analyst. I had the app generate the min and max ranges for three channels.

MATLAB code:
% Define thresholds for channel 1 based on histogram settings
channel1Min = 0.995;
channel1Max = 0.005;
% Define thresholds for channel 2 based on histogram settings
channel2Min = 0.821;
channel2Max = 0.872;
% Define thresholds for channel 3 based on histogram settings
channel3Min = 0.565;
channel3Max = 0.620;
% Create mask based on chosen histogram thresholds
BW = ( (I(:,:,1) >= channel1Min) | (I(:,:,1) <= channel1Max) ) & ...
  (I(:,:,2) >= channel2Min ) & (I(:,:,2) <= channel2Max) & ...
  (I(:,:,3) >= channel3Min ) & (I(:,:,3) <= channel3Max);

 I just learnt something new about Matlab tonight. As I mentioned in my question, I would appreciate it if you could show me where in my original coding I could implement the threshold ranges to get the output. Could you help me out please? I am still in the  learning process of image segmentation.

Thanks, Shyam