How to Detect and Track Red, Green and Blue Objects in Live Video in MATLAB
11/15/2013
2,756
How to Detect and Track Red, Green and Blue Objects in Live Video in MATLAB

Hi everyone, In this project, I have done some enhancement of my previous project: How to Detect and Track Red Objects in Live Video in MATLAB. In this project not only red color, but also green and blue color can be detected and tracked. The basic theory behind it can be found there. The procedure for red detection has been repeated for green and blue detection as well. So here, I am only giving the code you need.

MATLAB CODE

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Program Name : Red, Green and Blue Object Detection and Tracking
% Author : Arindam Bose
% Version : 1.07
% Description : How to detect and track red, green and blue objects in Live Video
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Initialization
redThresh = 0.24; % Threshold for red detection
greenThresh = 0.05; % Threshold for green detection
blueThresh = 0.15; % Threshold for blue 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', 600, ...
'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);
hshapeinsGreenBox = vision.ShapeInserter('BorderColor', 'Custom', ... % Set Green box handling
'CustomBorderColor', [0 1 0], ...
'Fill', true, ...
'FillColor', 'Custom', ...
'CustomFillColor', [0 1 0], ...
'Opacity', 0.4);
hshapeinsBlueBox = vision.ShapeInserter('BorderColor', 'Custom', ... % Set Blue box handling
'CustomBorderColor', [0 0 1], ...
'Fill', true, ...
'FillColor', 'Custom', ...
'CustomFillColor', [0 0 1], ...
'Opacity', 0.4);
htextinsRed = vision.TextInserter('Text', 'Red : %2d', ... % Set text for number of blobs
'Location', [5 2], ...
'Color', [1 0 0], ... // red color
'Font', 'Courier New', ...
'FontSize', 14);
htextinsGreen = vision.TextInserter('Text', 'Green : %2d', ... % Set text for number of blobs
'Location', [5 18], ...
'Color', [0 1 0], ... // green color
'Font', 'Courier New', ...
'FontSize', 14);
htextinsBlue = vision.TextInserter('Text', 'Blue : %2d', ... % Set text for number of blobs
'Location', [5 34], ...
'Color', [0 0 1], ... // blue color
'Font', 'Courier New', ...
'FontSize', 14);
htextinsCent = vision.TextInserter('Text', '+ X:%4d, Y:%4d', ... % set text for centroid
'LocationSource', 'Input port', ...
'Color', [1 1 0], ... // yellow color
'Font', 'Courier New', ...
'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 < 300)
rgbFrame = step(vidDevice); % Acquire single frame
rgbFrame = flipdim(rgbFrame,2); % obtain the mirror image for displaying
diffFrameRed = imsubtract(rgbFrame(:,:,1), rgb2gray(rgbFrame)); % Get red component of the image
diffFrameRed = medfilt2(diffFrameRed, [3 3]); % Filter out the noise by using median filter
binFrameRed = im2bw(diffFrameRed, redThresh); % Convert the image into binary image with the red objects as white
diffFrameGreen = imsubtract(rgbFrame(:,:,2), rgb2gray(rgbFrame)); % Get green component of the image
diffFrameGreen = medfilt2(diffFrameGreen, [3 3]); % Filter out the noise by using median filter
binFrameGreen = im2bw(diffFrameGreen, greenThresh); % Convert the image into binary image with the green objects as white
diffFrameBlue = imsubtract(rgbFrame(:,:,3), rgb2gray(rgbFrame)); % Get blue component of the image
diffFrameBlue = medfilt2(diffFrameBlue, [3 3]); % Filter out the noise by using median filter
binFrameBlue = im2bw(diffFrameBlue, blueThresh); % Convert the image into binary image with the blue objects as white
[centroidRed, bboxRed] = step(hblob, binFrameRed); % Get the centroids and bounding boxes of the red blobs
centroidRed = uint16(centroidRed); % Convert the centroids into Integer for further steps
[centroidGreen, bboxGreen] = step(hblob, binFrameGreen); % Get the centroids and bounding boxes of the green blobs
centroidGreen = uint16(centroidGreen); % Convert the centroids into Integer for further steps
[centroidBlue, bboxBlue] = step(hblob, binFrameBlue); % Get the centroids and bounding boxes of the blue blobs
centroidBlue = uint16(centroidBlue); % Convert the centroids into Integer for further steps
rgbFrame(1:50,1:90,:) = 0; % put a black region on the output stream
vidIn = step(hshapeinsRedBox, rgbFrame, bboxRed); % Instert the red box
vidIn = step(hshapeinsGreenBox, vidIn, bboxGreen); % Instert the green box
vidIn = step(hshapeinsBlueBox, vidIn, bboxBlue); % Instert the blue box
for object = 1:1:length(bboxRed(:,1)) % Write the corresponding centroids for red
centXRed = centroidRed(object,1); centYRed = centroidRed(object,2);
vidIn = step(htextinsCent, vidIn, [centXRed centYRed], [centXRed-6 centYRed-9]);
end
for object = 1:1:length(bboxGreen(:,1)) % Write the corresponding centroids for green
centXGreen = centroidGreen(object,1); centYGreen = centroidGreen(object,2);
vidIn = step(htextinsCent, vidIn, [centXGreen centYGreen], [centXGreen-6 centYGreen-9]);
end
for object = 1:1:length(bboxBlue(:,1)) % Write the corresponding centroids for blue
centXBlue = centroidBlue(object,1); centYBlue = centroidBlue(object,2);
vidIn = step(htextinsCent, vidIn, [centXBlue centYBlue], [centXBlue-6 centYBlue-9]);
end
vidIn = step(htextinsRed, vidIn, uint8(length(bboxRed(:,1)))); % Count the number of red blobs
vidIn = step(htextinsGreen, vidIn, uint8(length(bboxGreen(:,1)))); % Count the number of green blobs
vidIn = step(htextinsBlue, vidIn, uint8(length(bboxBlue(:,1)))); % Count the number of blue 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;

To download the source code from MATLAB CENTRAL Community Click Here: How to Detect and Track Red, Green and Blue Colored Object in LIVE Video

You can watch the video tutorial also:

About the author

Scientific History Blog Writer • Art enthusiast and Illustrator • Amateur Photographer • Biker and Hiker • Beer Enthusiast • Electrical Engineer • Chicago

One comment
David
10/26/2017

Hi,
How do you know the threshold for each color?
Thank you!

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