Why for 2nd loop data not running for ip camera first

Question

MOHAMMAD AZRUL AIMAN 2021-1-12

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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/714598-why-for-2nd-loop-data-not-running-for-ip-camera-first

评论： MOHAMMAD AZRUL AIMAN 2021-1-12

Hi, i got some problem. i just write a code to compare test image and reference image. my idea is the reference image are already in the directory while the test image will be capture from ip camera. i want to loop my code 5 time, at first loop ip cam will actived and scan for green ROI. then the image will be caputure and save to directory by given name of it. so here the problem occured. when continue to loop2, the ip camera will be skip, and the code create new image based on data before not current data .

the process for 2nd loop should be like first loop. ip camera actived, scan for green ROI, save the image then running other function. So, may someone see my code and explain why the code not work as my plan

cam = ipcam('http://192.168.0.102:8080/video'); 
framesAcquired = 0;
H=0;
i=0;
    
a= imread('testing.png');
I=rgb2hsv(a); %Convert RGB to HSV
S=I(:,:,2);
S=im2double(S);
% Threshold the image
level = graythresh(S); %Otsu' Method
BW = im2bw(S,level);
A=im2double(a);
P=2000;
BW = bwareaopen(BW,P); %Remove small pixel
% Histogram Red, Green, Blue
R=A(:,:,1);
G=A(:,:,2);
B=A(:,:,3);
dR=R.*BW;
dG=G.*BW;
dB=B.*BW;
rgb=im2double(I);
rgb(:,:,1)=dR;
rgb(:,:,2)=dG;
rgb(:,:,3)=dB;
ReferenceImage=rgb;
%H=H+1;figure(H);
%imshow(ReferenceImage);
while(i<=5) %value sample to test
while (framesAcquired <= 50)   
    
      data = snapshot(cam); 
      framesAcquired = framesAcquired + 1;    
      diff_im = imsubtract(data(:,:,2),rgb2gray(data));  % subtracting green component from the gray image
      diff_im = medfilt2(diff_im, [3 3]);             % used in image processing to reduce noise and for filtering
      diff_im = im2bw(diff_im,0.12);                   % convert image to binary image
      stats = regionprops(diff_im, 'BoundingBox', 'Centroid');  % measures a set of properties for each connected component in the binary image
      drawnow;
      imshow(data);
      hold on  
      for object = 1:length(stats)
          bb = stats(object).BoundingBox;
          bc = stats(object).Centroid;
          rectangle('Position',bb,'EdgeColor','b','LineWidth',2)
          plot(bc(1),bc(2), '-m+')       
      end
end
%imwrite(data, 'testing.png');
imwrite(data,sprintf('im%d.jpg',i))
%b= imread('%d.jpg',i);
b = imread(['D:\SEMESTER 5\idp\Ip camera Object Detect\im' num2str(i) '.jpg']);
I=rgb2hsv(b); %Convert RGB to HSV
S=I(:,:,2);
S=im2double(S);
% Threshold the image
level = graythresh(S); %Otsu' Method
BW = im2bw(S,level);
A=im2double(b);
P=2000;
BW = bwareaopen(BW,P); %Remove small pixel
% Histogram Red, Green, Blue
R=A(:,:,1);
G=A(:,:,2);
B=A(:,:,3);
dR=R.*BW;
dG=G.*BW;
dB=B.*BW;
rgb=im2double(I);
rgb(:,:,1)=dR;
rgb(:,:,2)=dG;
rgb(:,:,3)=dB;
TestImage=rgb;
H=H+1;figure(H);
imshow(TestImage);
% Image Comparing method
%------------------------------------------------------&
SubtractedImage = double(ReferenceImage)- double(TestImage);
%H=H+1;figure(H)
%imshow(SubtractedImage, []);
% k-segment method
%---------------------------------------------------%
lab_he = rgb2lab(SubtractedImage);
ab = lab_he(:,:,2:3);
ab = im2single(ab);
nColors = 5;
% repeat the clustering 3 times to avoid local minima
pixel_labels = imsegkmeans(ab,nColors,'NumAttempts',5);
%H=H+1;figure(H)
%imshow(pixel_labels, []);
t = graythresh(pixel_labels);
BW1 = imbinarize(pixel_labels,t);
%H=H+1;figure(H)
%imshow(BW1)
%Remove small Pixel
%---------------------------------------------------------%
Removesmallpixel = BW1;
BW2 = bwareaopen(Removesmallpixel, 700);
%H=H+1;figure(H)
%imshow(BW2);
% Find biggest blops(pixel)
%--------------------------------------------------%
BW3 = BW2;
CC = bwconncomp(BW3);
numPixels = cellfun(@numel,CC.PixelIdxList);
[biggest,idx] = max(numPixels);
%make background become 0
mask = BW3 > 0.5;
% Now everywhere that mask is true, set the original image to zero there.
BW3(mask) = 0;
disp('No contamination! Passes!')
disp('=======================================================')
disp('=======================================================')
disp('=======================================================')
%contamination area become 1
BW3(CC.PixelIdxList{idx}) = 1 ;
H=H+1;figure(H)
imshow(BW3);
%----------------------------------------------%
Measurements = regionprops(BW3, 'Area');
Area2       = [Measurements.Area];
% Perimeter2  = [Measurements.Perimeter];
% MajorAxis2  = [Measurements.MajorAxisLength];
% Extent2     = [Measurements.Extent];
Area_Testing_Shape       = sum(Area2)/10000; %devide by 10k to get smaller value
% Perimeter_Testing_Shape  = sum(Perimeter2);
% MajorAxis_Testing  = sum(MajorAxis2);
% Extent_Testing     = sum(Extent2);
fprintf('\t Area_Testing_Shape   = %g\n',Area_Testing_Shape );
% fprintf('\t Perimeter_Testing  = %g\n',Perimeter_Testing);
% fprintf('\t MajorAxis_Testing  = %g\n',MajorAxis_Testing);
% fprintf('\t Extent_Testing     = %g\n',Extent_Testing);
disp('=======================================================')
if (Area_Testing_Shape >= 9.7937)
    disp('Contamination Detected! Need Eye inspection')
    
elseif (2.0891 >= Area_Testing_Shape <= 9.7936)
    disp('Contamination Detected')
    
else 
    disp('Passed!')
end
disp('=======================================================')
disp('=======================================================')
disp('=======================================================')
i = i + 1;
end