MATLAB: How to to make a car park shows different colors for each dots using matlab

car parkcolor dotsImage Processing Toolbox

I convert my car park image to binary image and clear the unwanted white dots/region to get this image:

This is my original image with 10 green dots:

This is my codes:

    sceneImage = imread('nocars10green.jpg');
    figure;
    imshow(sceneImage);
    hsvscene = rgb2hsv (sceneImage);
    figure;
    imshow (hsvscene);
    grayscene = rgb2gray (hsvscene);
    figure;
    imshow (grayscene);
    bwScene = im2bw (grayscene);
    figure;
    imshow (bwScene);
    str = strel('disk',4)
    bw = imerode(bwScene,str)
    figure;
    imshow (bw);

How do I convert the binary image after erode so that I can show different colors for different dots?

I read in this journal.

Al-Kharusi, Hilal, and Ibrahim Al-Bahadly. "Intelligent parking management system based on image processing." World Journal of Engineering and Technology 2014 (2014).

it is mentioned:

if `(newmatrix(y,x) > 0)` % an object is there, if `(e(newmatrix(y,x)) = 0)` this object has not been seen `(newmatrix(y,x)) = x;` make the value and index 3 equal to the current `X` coordinate.

and this is their output image:

which they convert from this image:

But I don't understand how it works. Can anyone explain to me how it work and how to write the commands to convert my binary image to get the same as their output image in order to get different colors of each dots?

or if there is any other way to convert it?

Best Answer

You can label your binary image and then convert it to colored image like this

labeledImage = bwlabel(binaryImage);
coloredDots = label2rgb(labeledImage, 'hsv');

Then extract the color channels of your rgb image:

% Extract the individual red, green, and blue color channels.

redChannel = rgbImage(:, :, 1);
greenChannel = rgbImage(:, :, 2);
blueChannel = rgbImage(:, :, 3);
% Extract the individual red, green, and blue color channels.
redChannelDots = coloredDots (:, :, 1);
greenChannelDots = coloredDots (:, :, 2);
blueChannelDots = coloredDots (:, :, 3);

Then assign the colors in the dots mask

redChannel(binaryImage) = redChannelDots(binaryImage);
greenChannel(binaryImage) = rgreenChannelDots(binaryImage);
blueChannel(binaryImage) = blueChannelDots(binaryImage);

Then reassemble the new RGB image from the channels.

% Recombine separate color channels into a single, true color RGB image.
rgbImage = cat(3, redChannel, greenChannel, blueChannel);

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MATLAB: Binary Image – Black region detection

Mohsina, try this:

clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
clear;  % Erase all existing variables. Or clearvars if you want.
workspace;  % Make sure the workspace panel is showing.
format short g;
format compact;
fontSize = 25;
%===============================================================================

% Get the name of the image the user wants to use.
baseFileName = 'image1.png';
% Get the full filename, with path prepended.
folder = []; % Determine where demo folder is (works with all versions).
fullFileName = fullfile(folder, baseFileName);
%===============================================================================
% Read in a demo image.
grayImage = imread(fullFileName);
% Get the dimensions of the image.
% numberOfColorChannels should be = 1 for a gray scale image, and 3 for an RGB color image.
[rows, columns, numberOfColorChannels] = size(grayImage)
if numberOfColorChannels > 1
  % It's not really gray scale like we expected - it's color.
  % Use weighted sum of ALL channels to create a gray scale image.
  grayImage = rgb2gray(grayImage);
  % ALTERNATE METHOD: Convert it to gray scale by taking only the green channel,
  % which in a typical snapshot will be the least noisy channel.
  % grayImage = grayImage(:, :, 2); % Take green channel.
end
% Display the image.



subplot(2, 2, 1);
imshow(grayImage, []);
axis on;
axis image;
caption = sprintf('Original Gray Scale Image');
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
hp = impixelinfo();
% Set up figure properties:
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'OuterPosition', [0, 0, 1, 1]);
% Get rid of tool bar and pulldown menus that are along top of figure.
% set(gcf, 'Toolbar', 'none', 'Menu', 'none');
% Give a name to the title bar.
set(gcf, 'Name', 'Demo by ImageAnalyst', 'NumberTitle', 'Off')
drawnow;
% Create binary image of the black blobs from grayscale image.
binaryImage = grayImage == 0;
% Get rid of the background.
binaryImage = imclearborder(binaryImage);
% Display the image.
subplot(2, 2, 2);
imshow(binaryImage, []);
axis on;
axis image;
title('Binary Image', 'FontSize', fontSize, 'Interpreter', 'None');
% Label the blobs
[labeledImage, numBlobs] = bwlabel(binaryImage);
% Display the image.
subplot(2, 2, 2);
imshow(binaryImage, []);
axis on;
axis image;
title('Binary Image', 'FontSize', fontSize, 'Interpreter', 'None');
% Let's assign each blob a different color to visually show the user the distinct blobs.
coloredLabels = label2rgb (labeledImage, 'hsv', 'k', 'shuffle'); % pseudo random color labels
% coloredLabels is an RGB image.  We could have applied a colormap instead (but only with R2014b and later)
subplot(2, 2, 3);
imshow(coloredLabels);
axis on;
axis image; % Make sure image is not artificially stretched because of screen's aspect ratio.
caption = sprintf('Pseudo colored labels, from label2rgb().');
title(caption, 'FontSize', fontSize);
drawnow;
% Make measurements of bounding box.
props = regionprops(labeledImage, 'BoundingBox');
% Display the image.
subplot(2, 2, 4);
imshow(binaryImage, []);
axis on;
axis image;
title('Binary Image with Boxes', 'FontSize', fontSize, 'Interpreter', 'None');
% Display the bounding boxes around them.
hold on;
for k = 1 : numBlobs
  thisBoundingBox = props(k).BoundingBox
  rectangle('Position', thisBoundingBox, ...
    'EdgeColor', 'c', 'LineWidth', 2);
end

MATLAB: Read three different RGB band and Swap the Band

Try this:

% Extract the individual red, green, and blue color channels.
redChannel = rgbImage(:, :, 1);
greenChannel = rgbImage(:, :, 2);
blueChannel = rgbImage(:, :, 3);
% Now swap around in any way you want.
newRedChannel = greenChannel;
newGreenChannel = blueChannel; 
newBlueChannel = redChannel;
% Recombine separate color channels into a single, true color RGB image.
NewRgbImage = cat(3, newRedChannel, newGreenChannel, newBlueChannel);

Best Answer

Related Solutions

MATLAB: Binary Image – Black region detection

MATLAB: Read three different RGB band and Swap the Band

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