How to apply Otsu method to a stacked images

Question

Meshooo 2012-10-16

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/50967-how-to-apply-otsu-method-to-a-stacked-images

编辑： Meshooo 2014-1-23

Dear all,

I have 21 RGB microscopic images located in one folder. I want to apply the Otsu thresholding to each image in the folder (each image has different Otsu thresholding value).

How to make a "for loop" applied to the 21 images?

I tried this code but it finds the threshold value of the first image and applies it to all 21 images.

Any idea?

Meshoo

*****************************************************************

files = dir('*.tif');

for k = 1:(numel(files));

              thresh = [];
              image = imread(files(k).name);
              thresh = graythresh(image);
              newImage = im2bw(image, thresh);
              imwrite(newImage, ['NewImage\', files(k).name,]);

end

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Answer 1

Image Analyst 2012-10-16

0
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/50967-how-to-apply-otsu-method-to-a-stacked-images#answer_62126

编辑：Image Analyst 2012-10-16

在 MATLAB Online 中打开

Why are you applying monochrome thresholding to RGB images? You need to extract a color channel first, or use rgb2gray().

Assuming they're monochrome, I don't see any reason why this would not work. Take the semicolon off this line:

thresh = graythresh(image)

and see what values get written to the command window.

Also, don't use image as the name of your variable because you'll blow away the built-in image() function.

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Meshooo 2012-10-23

编辑：Image Analyst 2012-10-23

在 MATLAB Online 中打开

Humm..It is working very well now after removing the semicolon. My code is below.

I want to do the following steps:

Step1: read the whole tif images in the folder

Step2: get the green channel of each image

Step3: apply the Otsu thresholding to those green channels for binarization

Step4: find the unity of all these binary images in step3 together

I'm having problem how to do step4. In manual cases, if you have 3 images then the unity of these 3 images is

unityGreen = image_1 | image_2 | image_3;

Do you have any idea how do the unity for those binary images after we wrote them in the NewImage folder?

My current code is as follows:

files = dir('*.tif');  
for k = 1:(numel(files));
  imageI = imread(files(k).name);
  imageGreen = imageI(:,:,2);    
  threshGreen = [];
  threshGreen = graythresh(imageGreen)
  newImage = im2bw(imageGreen, threshGreen);
  imwrite(newImage, ['NewImage\', files(k).name,]);
end
Unity_Green = ??

Thank you in advance..

Sincerely, Sami

Image Analyst 2012-10-23

编辑：Image Analyst 2012-10-24

在 MATLAB Online 中打开

Why can't you just say:

clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
imtool close all;  % Close all imtool figures.
clear;  % Erase all existing variables.
workspace;  % Make sure the workspace panel is showing.
format longg;
format compact;
fontSize = 14;
folder = 'C:\Users\Mustafa\Pictures';
files = dir(fullfile(folder, '*.tif'));
for k = 1:(numel(files));
  fullFileName = fullfile(folder, files(k).name);
  rgbImage = imread(fullFileName);
  [rows columns numberOfColorChannels] = size(rgbImage);
  subplot(2, 2, 1);
  imshow(rgbImage);
  title('RGB Image');
  % Get dimensions/size.
  if k == 1
    % Enlarge figure to full screen.
    set(gcf, 'units','normalized','outerposition',[0 0 1 1]);
    [rows1 columns1 numberOfColorChannels1] = size(rgbImage);
  end
  % Get green channel or entire image if monochrome.
  if numberOfColorChannels > 1
    greenChannel = rgbImage(:,:,2);
  else
    greenChannel = rgbImage; % It's really monochrome
  end
  % Resize if necessary.
  if rows1~=rows || columns1 ~= columns
    greenChannel = imresize(greenChannel, [rows1 columns1]);
  end
  % Threshold via Otsu.
  greenThreshold = graythresh(greenChannel);
  binaryImage = im2bw(greenChannel, greenThreshold);
  % Accumulate into overall binary image.
  if k == 1
    Unity_Green = binaryImage;
    % Enlarge figure to full screen.
    set(gcf, 'units','normalized','outerposition',[0 0 1 1]);
  else
    Unity_Green = Unity_Green | binaryImage;
  end
  subplot(2, 2, 2);
  imshow(binaryImage);
  title('Binary Image');
  subplot(2, 2, 3);
  imshow(Unity_Green);
  title('Unity_Green Image');
  message = sprintf('Do you want to continue');
  button = questdlg(message, 'Continue?', 'Yes', 'No', 'Yes');
  drawnow;  % Refresh screen to get rid of dialog box remnants.
  if strcmpi(button, 'No')
    break;
  end
end
% imwrite(binaryImage, 'NewImage\Unity_Green.png');

Meshooo 2012-12-13

在 MATLAB Online 中打开

Hi again Image Analyst, I hope you still remember my old programing problem. I wanted to continue the same program but I am having a problem for how to use the for loop.

Last time you helped me to do the following 4 steps:

Step1: read the whole tif images in the folder

Step2: get the green channel of each image

Step3: apply the Otsu thresholding to those green channels for binarization

Step4: find the unity of all these binary images in step3 together

Step5: Apply a simple morphological filter to the image generated from step4 (thickening, bridging, opening, and closing)

the code for the above 5 steps can be written as follows:

%%STEP-1****************** Load Image ***************************
dname = which (uigetfile( {...
    '*.jpg;*.tif;*.gif;*.bmp;*.png', 'All image files(*.jpg,*.tif,*.gif,*.bmp,*.png)';
    '*.jpg;*.jpeg', 'JPEG files(*.jpg)';
    '*.gif', 'GIF files(*.gif)';
    '*.tif;*.tiff', 'TIFF files(*.tif)';
    '*.bmp', 'BMP files(*.bmp)';
    '*.png', 'PNG files(*.png)';
    '*.*', 'All Files (*.*)'}, 'Open an image'));
%
filelist = dir([fileparts(dname) filesep '*.tif']);
fileNames = {filelist.name}';
%%STEP2 to 5************* Loop Images **************************
for k = 1:(numel(filelist));
    imageI = imread(filelist(k).name);
    imageGreen = imageI(:,:, 2); %Find the green channel
      threshGreen = graythresh(imageGreen);
      if threshGreen < 0.05;  %to segment weak signal
          threshGreen = 0.1;
      end
      newImage = im2bw(imageGreen, threshGreen);  %Otsu Thresholding 
      if k ==1
          Unity_Green = newImage;
      else
          Unity_Green = Unity_Green | newImage; % Sum of all Green Channels
          se = strel('square',6); % Morphological Filter
          BW1_G = Unity_Green;
          BW2_G = Unity_Green; 
          BW1_G = bwmorph(BW1_G,'thicken');
          BW2_G = bwmorph(BW2_G,'bridge');
          BW3_G = imadd(BW1_G,BW2_G);
          fo_G = imopen(BW3_G, se);
          BW_G_F = imclose(fo_G, se);
          BW_G = im2bw(BW_G_F);
          [L, num] = bwlabel(BW_G, 8);  % Labeling using 8 connectivity
      end
  end

Meshooo 2012-12-13

编辑：Meshooo 2012-12-13

在 MATLAB Online 中打开

Now I want to add few more steps as follows:

Step6: find the centroid of all objects in the image we obtained from Step5 (BW_G). This can be written as:

s  = regionprops(BW_G, 'centroid');
centroids = cat(1, s.Centroid);
imtool(BW_G)
hold(imgca,'on')
plot(imgca,centroids(:,1), centroids(:,2), 'r.')
hold(imgca,'off')

Step7: multiply the binary image (BW_G) that we obtained from step 5 with each green channel of the input 21 images. Then apply a 3x3 median filter to every image. How to make a for loop to do that? I did it without for loop and it was very long as follows. G_1 is the green channel of the first image, and G_2 is the green channel of the second image and so forth.

space_1 = immultiply(BW_G, G_1);
Mean_Filter_1 = medfilt2(space_1,[3 3]); 
space_2 = immultiply(BW_G, G_2);
Mean_Filter_2 = medfilt2(space_2,[3 3]);
space_3 = immultiply(BW_G, G_3);
Mean_Filter_3 = medfilt2(space_3,[3 3]);  
space_4 = immultiply(BW_G, G_4);
Mean_Filter_4 = medfilt2(space_4,[3 3]);
space_5 = immultiply(BW_G, G_5);
Mean_Filter_5 = medfilt2(space_5,[3 3]);
space_6 = immultiply(BW_G, G_6);
Mean_Filter_6 = medfilt2(space_6,[3 3]);
space_7 = immultiply(BW_G, G_7);
Mean_Filter_7 = medfilt2(space_7,[3 3]);
space_8 = immultiply(BW_G, G_8);
Mean_Filter_8 = medfilt2(space_8,[3 3]);
space_9 = immultiply(BW_G, G_9);
Mean_Filter_9 = medfilt2(space_9,[3 3]);
space_10 = immultiply(BW_G, G_10);
Mean_Filter_10 = medfilt2(space_10,[3 3]);
space_11 = immultiply(BW_G, G_11);
Mean_Filter_11 = medfilt2(space_11,[3 3]);  
space_12 = immultiply(BW_G, G_12);
Mean_Filter_12 = medfilt2(space_12,[3 3]);
space_13 = immultiply(BW_G, G_13);
Mean_Filter_13 = medfilt2(space_13,[3 3]);  
space_14 = immultiply(BW_G, G_14);
Mean_Filter_14 = medfilt2(space_14,[3 3]);
space_15 = immultiply(BW_G, G_15);
Mean_Filter_15 = medfilt2(space_15,[3 3]);
space_16 = immultiply(BW_G, G_16);
Mean_Filter_16 = medfilt2(space_16,[3 3]);
space_17 = immultiply(BW_G, G_17);
Mean_Filter_17 = medfilt2(space_17,[3 3]);
space_18 = immultiply(BW_G, G_18);
Mean_Filter_18 = medfilt2(space_18,[3 3]);
space_19 = immultiply(BW_G, G_19);
Mean_Filter_19 = medfilt2(space_19,[3 3]);
space_20 = immultiply(BW_G, G_20);
Mean_Filter_20 = medfilt2(space_20,[3 3]);

Meshooo 2012-12-13

编辑：Meshooo 2012-12-13

在 MATLAB Online 中打开

Step8: To find the intensity value of the determined central point in each object of the green channels. In my case I have 21 images and therefore 21 green channel images. After segmentation we had 6 objects in the BW_G image that we found the centroid of each object in BW_G. Now I want to find the intensity value of this centroid in each green channel of the 20 input images. I did that without using the for loop and the code is as follows:

center = round(centroids(:,:,1)); %get the round value of all center pixles

Then applied to all the centroids of the 6 objects as follows:

%%******************** Centroid #1 *****************************
P_1 = impixel(Mean_Filter_1,(center(1,1)),(center(1,2)));   %the index intensity value of X,Y
PP_1 = P_1(:,1);
P_2 = impixel(Mean_Filter_2,(center(1,1)),(center(1,2)));   
PP_2 = P_2(:,1);
P_3 = impixel(Mean_Filter_3,(center(1,1)),(center(1,2)));   
PP_3 = P_3(:,1);
P_4 = impixel(Mean_Filter_4,(center(1,1)),(center(1,2)));   
PP_4 = P_4(:,1);
P_5 = impixel(Mean_Filter_5,(center(1,1)),(center(1,2)));   
PP_5 = P_5(:,1);
P_6 = impixel(Mean_Filter_6,(center(1,1)),(center(1,2)));   
PP_6 = P_6(:,1);
P_7 = impixel(Mean_Filter_7,(center(1,1)),(center(1,2)));   
PP_7 = P_7(:,1);
P_8 = impixel(Mean_Filter_8,(center(1,1)),(center(1,2)));   
PP_8 = P_8(:,1);
P_9 = impixel(Mean_Filter_9,(center(1,1)),(center(1,2)));   
PP_9 = P_9(:,1);
P_10 = impixel(Mean_Filter_10,(center(1,1)),(center(1,2)));   
PP_10 = P_10(:,1);
P_11 = impixel(Mean_Filter_11,(center(1,1)),(center(1,2)));   
PP_11 = P_11(:,1);
P_12 = impixel(Mean_Filter_12,(center(1,1)),(center(1,2)));   
PP_12 = P_12(:,1);
P_13 = impixel(Mean_Filter_13,(center(1,1)),(center(1,2)));   
PP_13 = P_13(:,1);
P_14 = impixel(Mean_Filter_14,(center(1,1)),(center(1,2)));   
PP_14 = P_14(:,1);
P_15 = impixel(Mean_Filter_15,(center(1,1)),(center(1,2)));   
PP_15 = P_15(:,1);
P_16 = impixel(Mean_Filter_16,(center(1,1)),(center(1,2)));   
PP_16 = P_16(:,1);
P_17 = impixel(Mean_Filter_17,(center(1,1)),(center(1,2)));   
PP_17 = P_17(:,1);
P_18 = impixel(Mean_Filter_18,(center(1,1)),(center(1,2)));   
PP_18 = P_18(:,1);
P_19 = impixel(Mean_Filter_19,(center(1,1)),(center(1,2)));   
PP_19 = P_19(:,1);
P_20 = impixel(Mean_Filter_20,(center(1,1)),(center(1,2)));   
PP_20 = P_20(:,1);
%%plot center#1
A = [PP_1, PP_2, PP_3, PP_4, PP_5, PP_6, PP_7, PP_8, PP_9, PP_10, PP_11,...
    PP_12, PP_13, PP_14, PP_15, PP_16, PP_17, PP_18, PP_19, PP_20];
%plot(A)
%%******************** Centroid #2 *****************************
P2_1 = impixel(Mean_Filter_1,(center(2,1)),(center(2,2)));   %the index intensity value of X,Y
PP2_1 = P2_1(:,1);
P2_2 = impixel(Mean_Filter_2,(center(2,1)),(center(2,2)));   
PP2_2 = P2_2(:,1);
P2_3 = impixel(Mean_Filter_3,(center(2,1)),(center(2,2)));   
PP2_3 = P2_3(:,1);
P2_4 = impixel(Mean_Filter_4,(center(2,1)),(center(2,2)));   
PP2_4 = P2_4(:,1);
P2_5 = impixel(Mean_Filter_5,(center(2,1)),(center(2,2)));   
PP2_5 = P2_5(:,1);
P2_6 = impixel(Mean_Filter_6,(center(2,1)),(center(2,2)));   
PP2_6 = P2_6(:,1);
P2_7 = impixel(Mean_Filter_7,(center(2,1)),(center(2,2)));   
PP2_7 = P2_7(:,1);
P2_8 = impixel(Mean_Filter_8,(center(2,1)),(center(2,2)));   
PP2_8 = P2_8(:,1);
P2_9 = impixel(Mean_Filter_9,(center(2,1)),(center(2,2)));   
PP2_9 = P2_9(:,1);
P2_10 = impixel(Mean_Filter_10,(center(2,1)),(center(2,2)));   
PP2_10 = P2_10(:,1);
P2_11 = impixel(Mean_Filter_11,(center(2,1)),(center(2,2)));   
PP2_11 = P2_11(:,1);
P2_12 = impixel(Mean_Filter_12,(center(2,1)),(center(2,2)));   
PP2_12 = P2_12(:,1);
P2_13 = impixel(Mean_Filter_13,(center(2,1)),(center(2,2)));   
PP2_13 = P2_13(:,1);
P2_14 = impixel(Mean_Filter_14,(center(2,1)),(center(2,2)));   
PP2_14 = P2_14(:,1);
P2_15 = impixel(Mean_Filter_15,(center(2,1)),(center(2,2)));   
PP2_15 = P2_15(:,1);
P2_16 = impixel(Mean_Filter_16,(center(2,1)),(center(2,2)));   
PP2_16 = P2_16(:,1);
P2_17 = impixel(Mean_Filter_17,(center(2,1)),(center(2,2)));   
PP2_17 = P2_17(:,1);
P2_18 = impixel(Mean_Filter_18,(center(2,1)),(center(2,2)));   
PP2_18 = P2_18(:,1);
P2_19 = impixel(Mean_Filter_19,(center(2,1)),(center(2,2)));   
PP2_19 = P2_19(:,1);
P2_20 = impixel(Mean_Filter_20,(center(2,1)),(center(2,2)));   
PP2_20 = P2_20(:,1);
%%plot center#2
A2 = [PP2_1, PP2_2, PP2_3, PP2_4, PP2_5, PP2_6, PP2_7, PP2_8, ...
    PP2_9, PP2_10, PP2_11, PP2_12, PP2_13, PP2_14, PP2_15, PP2_16, ...
    PP2_17, PP2_18, PP2_19, PP2_20];
%%******************** Centroid #3 *****************************
P3_1 = impixel(Mean_Filter_1,(center(3,1)),(center(3,2)));   %the index intensity value of X,Y
PP3_1 = P3_1(:,1);
P3_2 = impixel(Mean_Filter_2,(center(3,1)),(center(3,2)));   
PP3_2 = P3_2(:,1);
P3_3 = impixel(Mean_Filter_3,(center(3,1)),(center(3,2)));   
PP3_3 = P3_3(:,1);
P3_4 = impixel(Mean_Filter_4,(center(3,1)),(center(3,2)));   
PP3_4 = P3_4(:,1);
P3_5 = impixel(Mean_Filter_5,(center(3,1)),(center(3,2)));   
PP3_5 = P3_5(:,1);
P3_6 = impixel(Mean_Filter_6,(center(3,1)),(center(3,2)));   
PP3_6 = P3_6(:,1);
P3_7 = impixel(Mean_Filter_7,(center(3,1)),(center(3,2)));   
PP3_7 = P3_7(:,1);
P3_8 = impixel(Mean_Filter_8,(center(3,1)),(center(3,2)));   
PP3_8 = P3_8(:,1);
P3_9 = impixel(Mean_Filter_9,(center(3,1)),(center(3,2)));   
PP3_9 = P3_9(:,1);
P3_10 = impixel(Mean_Filter_10,(center(3,1)),(center(3,2)));   
PP3_10 = P3_10(:,1);
P3_11 = impixel(Mean_Filter_11,(center(3,1)),(center(3,2)));   
PP3_11 = P3_11(:,1);
P3_12 = impixel(Mean_Filter_12,(center(3,1)),(center(3,2)));   
PP3_12 = P3_12(:,1);
P3_13 = impixel(Mean_Filter_13,(center(3,1)),(center(3,2)));   
PP3_13 = P3_13(:,1);
P3_14 = impixel(Mean_Filter_14,(center(3,1)),(center(3,2)));   
PP3_14 = P3_14(:,1);
P3_15 = impixel(Mean_Filter_15,(center(3,1)),(center(3,2)));   
PP3_15 = P3_15(:,1);
P3_16 = impixel(Mean_Filter_16,(center(3,1)),(center(3,2)));   
PP3_16 = P3_16(:,1);
P3_17 = impixel(Mean_Filter_17,(center(3,1)),(center(3,2)));   
PP3_17 = P3_17(:,1);
P3_18 = impixel(Mean_Filter_18,(center(3,1)),(center(3,2)));   
PP3_18 = P3_18(:,1);
P3_19 = impixel(Mean_Filter_19,(center(3,1)),(center(3,2)));   
PP3_19 = P3_19(:,1);
P3_20 = impixel(Mean_Filter_20,(center(3,1)),(center(3,2)));   
PP3_20 = P3_20(:,1);
%%plot center#3
A3 = [PP3_1, PP3_2, PP3_3, PP3_4, PP3_5, PP3_6, PP3_7, PP3_8, ...
    PP3_9, PP3_10, PP3_11, PP3_12, PP3_13, PP3_14, PP3_15, PP3_16, ...
    PP3_17, PP3_18, PP3_19, PP3_20];
%%******************** Cetnroid #4 *****************************
P4_1 = impixel(Mean_Filter_1,(center(4,1)),(center(4,2)));   %the index intensity value of X,Y
PP4_1 = P4_1(:,1);
P4_2 = impixel(Mean_Filter_2,(center(4,1)),(center(4,2)));   
PP4_2 = P4_2(:,1);
P4_3 = impixel(Mean_Filter_3,(center(4,1)),(center(4,2)));   
PP4_3 = P4_3(:,1);
P4_4 = impixel(Mean_Filter_4,(center(4,1)),(center(4,2)));   
PP4_4 = P4_4(:,1);
P4_5 = impixel(Mean_Filter_5,(center(4,1)),(center(4,2)));   
PP4_5 = P4_5(:,1);
P4_6 = impixel(Mean_Filter_6,(center(4,1)),(center(4,2)));   
PP4_6 = P4_6(:,1);
P4_7 = impixel(Mean_Filter_7,(center(4,1)),(center(4,2)));   
PP4_7 = P4_7(:,1);
P4_8 = impixel(Mean_Filter_8,(center(4,1)),(center(4,2)));   
PP4_8 = P4_8(:,1);
P4_9 = impixel(Mean_Filter_9,(center(4,1)),(center(4,2)));   
PP4_9 = P4_9(:,1);
P4_10 = impixel(Mean_Filter_10,(center(4,1)),(center(4,2)));   
PP4_10 = P4_10(:,1);
P4_11 = impixel(Mean_Filter_11,(center(4,1)),(center(4,2)));   
PP4_11 = P4_11(:,1);
P4_12 = impixel(Mean_Filter_12,(center(4,1)),(center(4,2)));   
PP4_12 = P4_12(:,1);
P4_13 = impixel(Mean_Filter_13,(center(4,1)),(center(4,2)));   
PP4_13 = P4_13(:,1);
P4_14 = impixel(Mean_Filter_14,(center(4,1)),(center(4,2)));   
PP4_14 = P4_14(:,1);
P4_15 = impixel(Mean_Filter_15,(center(4,1)),(center(4,2)));   
PP4_15 = P4_15(:,1);
P4_16 = impixel(Mean_Filter_16,(center(4,1)),(center(4,2)));   
PP4_16 = P4_16(:,1);
P4_17 = impixel(Mean_Filter_17,(center(4,1)),(center(4,2)));   
PP4_17 = P4_17(:,1);
P4_18 = impixel(Mean_Filter_18,(center(4,1)),(center(4,2)));   
PP4_18 = P4_18(:,1);
P4_19 = impixel(Mean_Filter_19,(center(4,1)),(center(4,2)));   
PP4_19 = P4_19(:,1);
P4_20 = impixel(Mean_Filter_20,(center(4,1)),(center(4,2)));   
PP4_20 = P4_20(:,1);
%%plot center#4
A4 = [PP4_1, PP4_2, PP4_3, PP4_4, PP4_5, PP4_6, PP4_7, PP4_8, ...
    PP4_9, PP4_10, PP4_11, PP4_12, PP4_13, PP4_14, PP4_15, PP4_16, ...
    PP4_17, PP4_18, PP4_19, PP4_20];
%%******************** Centroid #5 *****************************
P5_1 = impixel(Mean_Filter_1,(center(5,1)),(center(5,2)));   %the index intensity value of X,Y
PP5_1 = P5_1(:,1);
P5_2 = impixel(Mean_Filter_2,(center(5,1)),(center(5,2)));   
PP5_2 = P5_2(:,1);
P5_3 = impixel(Mean_Filter_3,(center(5,1)),(center(5,2)));   
PP5_3 = P5_3(:,1);
P5_4 = impixel(Mean_Filter_4,(center(5,1)),(center(5,2)));   
PP5_4 = P5_4(:,1);
P5_5 = impixel(Mean_Filter_5,(center(5,1)),(center(5,2)));   
PP5_5 = P5_5(:,1);
P5_6 = impixel(Mean_Filter_6,(center(5,1)),(center(5,2)));   
PP5_6 = P5_6(:,1);
P5_7 = impixel(Mean_Filter_7,(center(5,1)),(center(5,2)));   
PP5_7 = P5_7(:,1);
P5_8 = impixel(Mean_Filter_8,(center(5,1)),(center(5,2)));   
PP5_8 = P5_8(:,1);
P5_9 = impixel(Mean_Filter_9,(center(5,1)),(center(5,2)));   
PP5_9 = P5_9(:,1);
P5_10 = impixel(Mean_Filter_10,(center(5,1)),(center(5,2)));   
PP5_10 = P5_10(:,1);
P5_11 = impixel(Mean_Filter_11,(center(5,1)),(center(5,2)));   
PP5_11 = P5_11(:,1);
P5_12 = impixel(Mean_Filter_12,(center(5,1)),(center(5,2)));   
PP5_12 = P5_12(:,1);
P5_13 = impixel(Mean_Filter_13,(center(5,1)),(center(5,2)));   
PP5_13 = P5_13(:,1);
P5_14 = impixel(Mean_Filter_14,(center(5,1)),(center(5,2)));   
PP5_14 = P5_14(:,1);
P5_15 = impixel(Mean_Filter_15,(center(5,1)),(center(5,2)));   
PP5_15 = P5_15(:,1);
P5_16 = impixel(Mean_Filter_16,(center(5,1)),(center(5,2)));   
PP5_16 = P5_16(:,1);
P5_17 = impixel(Mean_Filter_17,(center(5,1)),(center(5,2)));   
PP5_17 = P5_17(:,1);
P5_18 = impixel(Mean_Filter_18,(center(5,1)),(center(5,2)));   
PP5_18 = P5_18(:,1);
P5_19 = impixel(Mean_Filter_19,(center(5,1)),(center(5,2)));   
PP5_19 = P5_19(:,1);
P5_20 = impixel(Mean_Filter_20,(center(5,1)),(center(5,2)));   
PP5_20 = P5_20(:,1);
%%plot center#5
A5 = [PP5_1, PP5_2, PP5_3, PP5_4, PP5_5, PP5_6, PP5_7, PP5_8, ...
    PP5_9, PP5_10, PP5_11, PP5_12, PP5_13, PP5_14, PP5_15, PP5_16, ...
    PP5_17, PP5_18, PP5_19, PP5_20];
%%******************** Centroid #6 *****************************
P6_1 = impixel(Mean_Filter_1,(center(6,1)),(center(6,2)));   %the index intensity value of X,Y
PP6_1 = P6_1(:,1);
P6_2 = impixel(Mean_Filter_2,(center(6,1)),(center(6,2)));   
PP6_2 = P6_2(:,1);
P6_3 = impixel(Mean_Filter_3,(center(6,1)),(center(6,2)));   
PP6_3 = P6_3(:,1);
P6_4 = impixel(Mean_Filter_4,(center(6,1)),(center(6,2)));   
PP6_4 = P6_4(:,1);
P6_5 = impixel(Mean_Filter_5,(center(6,1)),(center(6,2)));   
PP6_5 = P6_5(:,1);
P6_6 = impixel(Mean_Filter_6,(center(6,1)),(center(6,2)));   
PP6_6 = P6_6(:,1);
P6_7 = impixel(Mean_Filter_7,(center(6,1)),(center(6,2)));   
PP6_7 = P6_7(:,1);
P6_8 = impixel(Mean_Filter_8,(center(6,1)),(center(6,2)));   
PP6_8 = P6_8(:,1);
P6_9 = impixel(Mean_Filter_9,(center(6,1)),(center(6,2)));   
PP6_9 = P6_9(:,1);
P6_10 = impixel(Mean_Filter_10,(center(6,1)),(center(6,2)));   
PP6_10 = P6_10(:,1);
P6_11 = impixel(Mean_Filter_11,(center(6,1)),(center(6,2)));   
PP6_11 = P6_11(:,1);
P6_12 = impixel(Mean_Filter_12,(center(6,1)),(center(6,2)));   
PP6_12 = P6_12(:,1);
P6_13 = impixel(Mean_Filter_13,(center(6,1)),(center(6,2)));   
PP6_13 = P6_13(:,1);
P6_14 = impixel(Mean_Filter_14,(center(6,1)),(center(6,2)));   
PP6_14 = P6_14(:,1);
P6_15 = impixel(Mean_Filter_15,(center(6,1)),(center(6,2)));   
PP6_15 = P6_15(:,1);
P6_16 = impixel(Mean_Filter_16,(center(6,1)),(center(6,2)));   
PP6_16 = P6_16(:,1);
P6_17 = impixel(Mean_Filter_17,(center(6,1)),(center(6,2)));   
PP6_17 = P6_17(:,1);
P6_18 = impixel(Mean_Filter_18,(center(6,1)),(center(6,2)));   
PP6_18 = P6_18(:,1);
P6_19 = impixel(Mean_Filter_19,(center(6,1)),(center(6,2)));   
PP6_19 = P6_19(:,1);
P6_20 = impixel(Mean_Filter_20,(center(6,1)),(center(6,2)));   
PP6_20 = P6_20(:,1);
%%plot center#6
A6 = [PP6_1, PP6_2, PP6_3, PP6_4, PP6_5, PP6_6, PP6_7, PP6_8, ...
    PP6_9, PP6_10, PP6_11, PP6_12, PP6_13, PP6_14, PP6_15, PP6_16, ...
    PP6_17, PP6_18, PP6_19, PP6_20];

Meshooo 2012-12-20

编辑：Meshooo 2012-12-20

在 MATLAB Online 中打开

Hi again and thank you for your reply. I am trying by myself and things are going well. However, I would like to ask you how to make two For-loops inside each other?

For example I want to load the whole 21 intensity images (Intensity) from the folder and find their intensity value in 6 points which I already know them.

I wrote the following program which works very well but I want to use a for loop because the number of points is not always 6.

Could you please check this code to make a for loop

   for k = 1:(numel(filelist)); 
        Intensity = imread(filelist(k).name);
        P_Centro_1 = []; %1st centroid
        P_Centro_1 = impixel(Intensity,(center(1,1)),(center(1,2)));
        P_Centro_1 = P_Centro_1(:,1); %Intensity value
        A1(:,k)= P_Centro_1;
        P_Centro_2 = []; %2nd centroid
        P_Centro_2 = impixel(Intensity,(center(2,1)),(center(2,2)));
        P_Centro_2 = P_Centro_2(:,1);
        A2(:,k)= P_Centro_2;
        P_Centro_3 = []; %3rd centroid
        P_Centro_3 = impixel(Intensity,(center(3,1)),(center(3,2)));
        P_Centro_3 = P_Centro_3(:,1);
        A3(:,k)= P_Centro_3;
        P_Centro_4 = []; %4th centroid
        P_Centro_4 = impixel(Intensity,(center(4,1)),(center(4,2)));
        P_Centro_4 = P_Centro_4(:,1);
        A4(:,k)= P_Centro_4;
        P_Centro_5 = []; %5th centroid
        P_Centro_5 = impixel(Intensity,(center(5,1)),(center(5,2)));
        P_Centro_5 = P_Centro_5(:,1);
        A5(:,k)= P_Centro_5;
        P_Centro_6 = []; %6th centroid
        P_Centro_6 = impixel(Intensity,(center(6,1)),(center(6,2)));
        P_Centro_6 = P_Centro_6(:,1);
        A6(:,k)= P_Centro_6;
    end
    hold on
    plot(A1,'b-')
    plot(A2,'c-')
    plot(A3,'g-')
    plot(A4,'y-')
    plot(A5,'r-')
    plot(A6,'m-')
    hold off

Thank you very much for your time.

Meshooo 2012-12-20

编辑：Meshooo 2012-12-20

在 MATLAB Online 中打开

The following program seems to be the answer, but how to store the results from every loop in A1?

for k = 1:21
    Intensity = imread(filelist(k).name);
    for c = 1:6
        P_Centro_1 = []; % list of centroids
        P_Centro_1 = impixel(Intensity,(center(c,1)),(center(c,2)));
        P_Centro_1 = P_Centro_1(:,1); %Intensity value
        A1(:,k)= P_Centro_1;
    end
end

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