How can I change this code to detect and track black objects of white background?

I got this code from the internet for detecting and tracking red objects, I made some modifications in it to detect black objects

function redObjectTrack()

%a = imaqhwinfo;
%[camera_name, camera_id, format] = getCameraInfo(a);

% Capture the video frames using the videoinput function
% You have to replace the resolution & your installed adaptor name.
vid = videoinput('winvideo',2);

% 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)

% 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(25*data(:,:,3), rgb2gray(data));
      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,10);

      % 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

The change I made is subtracting the blue color component and strengthening to act like black instead of subtracting the red colors components %diff_im = imsubtract(25*data(:,:,3), rgb2gray(data)); but my application is to detect black rope with knots on it, what I did is detecting the whole rope as a one object. how can I detect the knots on the rope so that each knot appear as a single object?? I'm taking input from the Webcam and the rope with knots looks like the attached image

%

Answer 1

[Image Analyst]

Usually when people ask for image processing advice, they show us the image. Failing that about all I can say is to try putting a ~ in front of the im2bw() to flip the foreground and background:

diff_im = ~im2bw(diff_im,0.18);

Or simply do

diff_im = diff_im < (0.18 * 255); % If it's an 8 bit image.

If not, then attach your image and we'll see what I can do.

[Ahmad Ali]

I've attached a snapshot from the video I'm taking as an input my question is that can I detect and track each individual knot as well as both ends of the rope

Answer 2

[Image Analyst]

See my attached code for tracking a green Sharpie marker in a video. Adapt the thresholds to get a red object instead.

See other color segmentation demos in my File Exchange: http://www.mathworks.com/matlabcentral/fileexchange/?term=authorid%3A31862&sort=downloads_desc

[Hershey Wiseman]

Could you answer this question when you get a chance please? https://www.mathworks.com/matlabcentral/answers/399980-how-do-i-change-my-program-to-recognizes-red-images-from-a-video-and-puts-a-red-box-around-it-to-gre?s_tid=prof_contriblnk

Answer 3

[Usman Ali]

How can i write code in matlab and Android development software for Plant disease detection and diagnosis