matlab android camera and object tracking

by refering to this code:

url = 'http://<ip address>/shot.jpg';
ss  = imread(url);
fh = image(ss);
while(1)
    ss  = imread(url);
    set(fh,'CData',ss);
    drawnow;
end

i able to display the video from android phone ( using app ip camera), and i dont know on how to combine this code with below code:

vid = videoinput('winvideo', 1);

% Set the properties of the video object
set(vid, 'FramesPerTrigger', Inf);
set(vid, 'ReturnedColorspace', 'rgb')
vid.FrameGrabInterval = 5;

%start the video aquisition here
start(vid)  ( here the video is taken from webcam, i want it to be taken from my android phone)

% Set a loop that stop after 100 frames of aquisition
while(vid.FramesAcquired<=200)

      % Get the snapshot of the current frame
      data = getsnapshot(vid);

      % Now to track red objects in real time
      % we have to subtract the red component 
      % from the grayscale image to extract the red components in the image.
      diff_im = imsubtract(data(:,:,1), rgb2gray(data));
      %Use a median filter to filter out noise
      diff_im = medfilt2(diff_im, [3 3]);
      % Convert the resulting grayscale image into a binary image.
      diff_im = im2bw(diff_im,0.18);

      % Remove all those pixels less than 300px
      diff_im = bwareaopen(diff_im,300);

      % Label all the connected components in the image.
      bw = bwlabel(diff_im, 8);

      % Here we do the image blob analysis.
      % We get a set of properties for each labeled region.
      stats = regionprops(bw, 'BoundingBox', 'Centroid');

      % Display the image
      imshow(data)

      hold on

      %This is a loop to bound the red objects in a rectangular box.
      for object = 1:length(stats)
          bb = stats(object).BoundingBox;
          bc = stats(object).Centroid;
          rectangle('Position',bb,'EdgeColor','r','LineWidth',2)
          plot(bc(1),bc(2), '-m+')
          a=text(bc(1)+15,bc(2), strcat('X: ', num2str(round(bc(1))), '    Y: ', num2str(round(bc(2)))));
          set(a, 'FontName', 'Arial', 'FontWeight', 'bold', 'FontSize', 12, 'Color', 'yellow');
      end

      hold off
  end
  % Both the loops end here.

% Stop the video aquisition.
stop(vid);

% Flush all the image data stored in the memory buffer.
flushdata(vid);

% Clear all variables
clear all

Answer 1

[Walter Roberson]

Replace

data = getsnapshot(vid);

with

data = imread(url);

[amirul]

vid = videoinput('winvideo', 1);
set(vid, 'FramesPerTrigger', Inf);
set(vid, 'ReturnedColorspace', 'rgb')
vid.FrameGrabInterval = 5;
start(vid)  
% Set a loop that stop after 100 frames of aquisition
while(vid.FramesAcquired<=200)

do i need yo change all this? thank you for ur answer. if it possible could u combine the code.

[Walter Roberson]

You don't need that. Replace it with

FramesAcquired = 0;

before the loop, and

while FramesAcquired <= 200

as the loop condition, and then after the urlread() add

FramesAcquired = FramesAcquired + 1;

[Diec Thuan]

Hey guy, can you explain to me what means CData, thank all!!

[Walter Roberson]

@Diec Thuan

CData is "Color Data" . This term is used for RGB color information, and it is also used for grayscale information, and it is also used for indices for pseudocolor (colormapped) images.

[Diec Thuan]

in the code, I don't see the declaration anywhere?

[Walter Roberson]

If you are talking about the code

fh = image(ss);
while(1)
    ss  = imread(url);
    set(fh,'CData',ss);
    drawnow;
end

then what that code is doing is updating the CData property associated with the fh variable, where the fh variable has been created as an image graphics object. The CData property is the part of image graphics objects that is used to store the information about what array of values is to be displayed. It is being initialized in this particular section of code according to whatever the initial value of ss was at the time fh was created.

Answer 2

[PIYUSH KUMAR]

Here's the working code of color detection using android camera:

url = 'http://192.168.0.100:8080/shot.jpg'; 
framesAcquired = 0;

while (framesAcquired <= 50)                   

      data = imread(url); 
      framesAcquired = framesAcquired + 1;    
      diff_im = imsubtract(data(:,:,1), rgb2gray(data));  % subtracting red 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,0.18);                   % 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
      hold off  

end
%stop(vid);    % to stop the video

%flushdata(vid);  % erase the data video

clear all

Answer 3

[Shahroze Hussain]

url = 'http://192.168.10.2:8080/shot.jpg';
ss  = imread(url);
fh = image(ss);

while(1)
    ss  = imread(url);
    set(fh,'CData',ss);
    drawnow;
end

foregroundDetector = vision.ForegroundDetector('NumGaussians', 3, ...
    'NumTrainingFrames', 50);
videoReader = vision.VideoFileReader('visiontraffic.avi');
for i = 1:150
    frame = step(videoReader); % read the next video frame
    foreground = step(foregroundDetector, frame);
end
%figure; 
%imshow(frame); 
%title('Video Frame');
%figure; 
%imshow(foreground); 
%title('Foreground');
se = strel('square', 3);
filteredForeground = imopen(foreground, se);
%figure;
%imshow(filteredForeground); 
%title('Clean Foreground');
blobAnalysis = vision.BlobAnalysis('BoundingBoxOutputPort', true, ...
    'AreaOutputPort', false, 'CentroidOutputPort', false, ...
    'MinimumBlobArea', 150);
bbox = step(blobAnalysis, filteredForeground);
result = insertShape(frame, 'Rectangle', bbox, 'Color', 'red');
numCars =  size(bbox, 1);

result = insertText(result, [10 10], numCars, 'BoxOpacity', 1, ...
    'FontSize', 14);
%figure; 
%imshow(result); 
%title('Detected Cars');
videoPlayer = vision.VideoPlayer('Name', 'Detected Cars');
videoPlayer.Position(3:4) = [650,400];  % window size: [width, height]
se = strel('square', 3); % morphological filter for noise removal

while ~isDone(videoReader)

      frame = step(videoReader); % read the next video frame

      % Detect the foreground in the current video frame
      foreground = step(foregroundDetector, frame);

      % Use morphological opening to remove noise in the foreground
      filteredForeground = imopen(foreground, se);

      % Detect the connected components with the specified minimum area, and
      % compute their bounding boxes
      bbox = step(blobAnalysis, filteredForeground);

      % Draw bounding boxes around the detected cars
      result = insertShape(frame, 'Rectangle', bbox, 'Color', 'red');

      % Display the number of cars found in the video frame
      numCars =  size(bbox,1);
      asciiChars = char(numCars+'A'-1);
      result = insertText(result, [10 10], asciiChars, 'BoxOpacity',1,...
          'FontSize', 14,'BoxColor','Green');
      step(videoPlayer, result);  % display the results
  end
   asciiChars = char(numCars+'A'-1)
  release(videoReader); % close the video file

How to combine these two codes

[Walter Roberson]

url = 'http://192.168.10.2:8080/shot.jpg';

foregroundDetector = vision.ForegroundDetector('NumGaussians', 3, ...
    'NumTrainingFrames', 50);
for i = 1:150
    frame = imread(url); % read the next video frame
    foreground = step(foregroundDetector, frame);
end

se = strel('square', 3);
filteredForeground = imopen(foreground, se);

videoPlayer = vision.VideoPlayer('Name', 'Detected Cars');
videoPlayer.Position(3:4) = [650,400];  % window size: [width, height]
se = strel('square', 3); % morphological filter for noise removal

while true

        frame = imread(url); % read the next video frame

        % Detect the foreground in the current video frame
        foreground = step(foregroundDetector, frame);

        % Use morphological opening to remove noise in the foreground
        filteredForeground = imopen(foreground, se);

        % Detect the connected components with the specified minimum area, and
        % compute their bounding boxes
        bbox = step(blobAnalysis, filteredForeground);

        % Draw bounding boxes around the detected cars
        result = insertShape(frame, 'Rectangle', bbox, 'Color', 'red');

        % Display the number of cars found in the video frame
        numCars =  size(bbox,1);
        asciiChars = char(numCars+'A'-1);
        result = insertText(result, [10 10], asciiChars, 'BoxOpacity',1,...
            'FontSize', 14,'BoxColor','Green');
        step(videoPlayer, result);  % display the results
    end
     asciiChars = char(numCars+'A'-1)

[Rohil Setia]

not working. it is showing that blobAnalysis as undefined.

[Walter Roberson]

You will need to add in

blobAnalysis = vision.BlobAnalysis('BoundingBoxOutputPort', true, ...
    'AreaOutputPort', false, 'CentroidOutputPort', false, ...
    'MinimumBlobArea', 150);