tracking objects with an IP webcam

Hello, I want realize a program in order to track and detect red object for example, using a smartphone's camera and an IP webcam. I've used this for streaming :

url = 'http://(adress IP ) /shot.jpg'; ss = imread(url); fh = image(ss); while(1) ss = imread(url); set(fh,'CData',ss); drawnow; end

Answer 1

[Abdelhamid ROCHDI]

I hope to combine it with this :

% Initialization
redThresh = 0.25; % Threshold for red detection
vidDevice = imaq.VideoDevice('winvideo', 1, 'YUY2_640x480', ... % Acquire input video stream
                  'ROI', [1 1 640 480], ...
                  'ReturnedColorSpace', 'rgb');
vidInfo = imaqhwinfo(vidDevice); % Acquire input video property
hblob = vision.BlobAnalysis('AreaOutputPort', false, ... % Set blob analysis handling
                              'CentroidOutputPort', true, ... 
                              'BoundingBoxOutputPort', true', ...
                              'MinimumBlobArea', 800, ...
                              'MaximumBlobArea', 3000, ...
                              'MaximumCount', 10);
hshapeinsRedBox = vision.ShapeInserter('BorderColor', 'Custom', ... % Set Red box handling
                                      'CustomBorderColor', [1 0 0], ...
                                      'Fill', true, ...
                                      'FillColor', 'Custom', ...
                                      'CustomFillColor', [1 0 0], ...
                                      'Opacity', 0.4);
htextins = vision.TextInserter('Text', 'Number of Red Object: %2d', ... % Set text for number of blobs
                                  'Location',  [7 2], ...
                                  'Color', [1 0 0], ... // red color
                                  'FontSize', 12);
htextinsCent = vision.TextInserter('Text', '+      X:%4d, Y:%4d', ... % set text for centroid
                                  'LocationSource', 'Input port', ...
                                  'Color', [1 1 0], ... // yellow color
                                  'FontSize', 14);
hVideoIn = vision.VideoPlayer('Name', 'Final Video', ... % Output video player
                              'Position', [100 100 vidInfo.MaxWidth+20 vidInfo.MaxHeight+30]);
nFrame = 0; % Frame number initialization

%% Processing Loop while(nFrame < 20) rgbFrame = step(vidDevice); % Acquire single frame rgbFrame = flipdim(rgbFrame,2); % obtain the mirror image for displaying diffFrame = imsubtract(rgbFrame(:,:,1), rgb2gray(rgbFrame)); % Get red component of the image diffFrame = medfilt2(diffFrame, [3 3]); % Filter out the noise by using median filter binFrame = im2bw(diffFrame, redThresh); % Convert the image into binary image with the red objects as white [centroid, bbox] = step(hblob, binFrame); % Get the centroids and bounding boxes of the blobs centroid = uint16(centroid); % Convert the centroids into Integer for further steps rgbFrame(1:20,1:165,:) = 0; % put a black region on the output stream vidIn = step(hshapeinsRedBox, rgbFrame, bbox); % Instert the red box for object = 1:1:length(bbox(:,1)) % Write the corresponding centroids centX = centroid(object,1); centY = centroid(object,2); vidIn = step(htextinsCent, vidIn, [centX centY], [centX-6 centY-9]); end vidIn = step(htextins, vidIn, uint8(length(bbox(:,1)))); % Count the number of blobs step(hVideoIn, vidIn); % Output video stream nFrame = nFrame+1; end %% Clearing Memory release(hVideoIn); % Release all memory and buffer used release(vidDevice); % clear all; clc;