Counting number of objects based on color

How do you make a script which codes for counting the number of objects based on color?

[Stephen23]

https://web.archive.org/web/20211221054448/https://www.mathworks.com/matlabcentral/answers/1614520-counting-number-of-objects-based-on-color

Answer 1

[Image Analyst]

Construct the 3-D histogram where you scan the image, getting the R, G, and B values and using those as an index into a histogram array. Then count the number of non-zero values. Something like

h = zeros(256,256,256);
[rows, columns, numberOfColorChannels] = size(rgbImage);
for col = 1 : columns
    for row = 1 : rows
        r = rgbImage(row, col, 1);
        g = rgbImage(row, col, 2);
        b = rgbImage(row, col, 3);
        h(r, g, b) = h(r, g, b) + 1;
    end
end
numColors = nnz(h)

Be aware that this counts unique colors even if they're only extremely slightly different. For example [100, 120, 140] is considered a different color than [101, 120, 140]. If you want wider bins than that you'll have to do it slightly differently. You could even use a clustering method like kmeans() to try to figure out some best number of clusters.

[curious dolphin]

hello @Image Analyst, what if i want to count the number of blue colored objects in a picture?

[Image Analyst]

See this:

% Demo by Image Analyst.
clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
clearvars;
workspace;  % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 16;
fprintf('Beginning to run %s.m ...\n', mfilename);
%-----------------------------------------------------------------------------------------------------------------------------------
% Read in image.
folder = [];
baseFileName = 'toys.jpeg';
fullFileName = fullfile(folder, baseFileName);
% Check if file exists.
if ~exist(fullFileName, 'file')
    % The file doesn't exist -- didn't find it there in that folder.
    % Check the entire search path (other folders) for the file by stripping off the folder.
    fullFileNameOnSearchPath = baseFileName; % No path this time.
    if ~exist(fullFileNameOnSearchPath, 'file')
        % Still didn't find it.  Alert user.
        errorMessage = sprintf('Error: %s does not exist in the search path folders.', fullFileName);
        uiwait(warndlg(errorMessage));
        return;
    end
end
rgbImage = imread(fullFileName);
[rows, columns, numberOfColorChannels] = size(rgbImage)
% Display the image.
subplot(2, 2, 1);
imshow(rgbImage, []);
axis('on', 'image');
hp = impixelinfo(); % Set up status line to see values when you mouse over the image.
caption = sprintf('Original RGB Image : "%s"\n%d rows by %d columns', baseFileName, rows, columns);
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
hp = impixelinfo(); % Set up status line to see values when you mouse over the image.
% Set up figure properties:
% Enlarge figure to full screen.
hFig1 = gcf;
hFig1.Units = 'Normalized';
hFig1.WindowState = 'maximized';
% 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.
hFig1.Name = 'Demo by Image Analyst';
%-----------------------------------------------------------------------------------------------------------------------------------
[mask, maskedRGBImage] = createMask(rgbImage);
% Find area of things
subplot(2, 2, 2);
props = regionprops(mask, 'Area')
allAreas = sort([props.Area], 'Descend')
histogram([props.Area], 100)
% Display the image.
subplot(2, 2, 2);
imshow(mask, []);
axis('on', 'image');
hp = impixelinfo(); % Set up status line to see values when you mouse over the image.
title('Initial Mask Image', 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
% Clean up the mask.
% Fill holes
mask = imfill(mask, 'holes');
% Get rid of small things.  Looks like things we're interested in are bigger than about 1000.
mask = bwareaopen(mask, 1000);
% Display final mask
subplot(2, 2, 3);
imshow(mask, []);
axis('on', 'image');
hp = impixelinfo(); % Set up status line to see values when you mouse over the image.
title('Final Mask', 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
% Find the properties of all the blobs.
props = regionprops(mask, 'BoundingBox', 'Centroid', 'Image')
numRegions = length(props)
%-----------------------------------------------------------------------
% Plot the borders of all the blobs in the overlay above the original image
% using the coordinates returned by bwboundaries().
% bwboundaries() returns a cell array, where each cell contains the row/column coordinates for an object in the image.
subplot(2, 2, 4);
imshow(rgbImage, []);
axis('on', 'image');
hp = impixelinfo(); % Set up status line to see values when you mouse over the image.
title('Objects Outlined', 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
% Here is where we actually get the boundaries for each blob.
boundaries = bwboundaries(mask);
% boundaries is a cell array - one cell for each blob.
% In each cell is an N-by-2 list of coordinates in a (row, column) format.  Note: NOT (x,y).
% Column 1 is rows, or y.    Column 2 is columns, or x.
numberOfBoundaries = size(boundaries, 1); % Count the boundaries so we can use it in our for loop
% Here is where we actually plot the boundaries of each blob in the overlay.
hold on; % Don't let boundaries blow away the displayed image.
for k = 1 : numberOfBoundaries
    thisBoundary = boundaries{k}; % Get boundary for this specific blob.
    x = thisBoundary(:,2); % Column 2 is the columns, which is x.
    y = thisBoundary(:,1); % Column 1 is the rows, which is y.
    plot(x, y, 'r-', 'LineWidth', 2); % Plot boundary in red.
end
hold off;
caption = sprintf('%d Outlines, from bwboundaries()', numberOfBoundaries);
title(caption, 'FontSize', fontSize);
axis('on', 'image'); % Make sure image is not artificially stretched because of screen's aspect ratio.
%-----------------------------------------------------------------------
% Plot bounding boxes over all blue blobs.
for k = 1 : numRegions
    thisBB = props(k).BoundingBox;
    rectangle('Position', thisBB, 'EdgeColor', 'r', 'LineWidth', 2)
end
%-----------------------------------------------------------------------
% Crop out individual images.
plotRows = ceil(sqrt(numRegions));
figure;
outputFolder = fullfile(pwd, 'Individual Images');
if ~isfolder(outputFolder)
    mkdir(outputFolder);
end
for k = 1 : numRegions
    thisImage = imcrop(rgbImage, props(k).BoundingBox);
    % Get the mask for this cropped image.
    thisMask = props(k).Image;
    % For some reason, thisMask is one pixel narrower and taller than thisImage.  Expand it.
    thisMask(end+1, end+1) = false;
    % Mask out background and other objects.
    thisImage = bsxfun(@times, thisImage, cast(thisMask, 'like', rgbImage)); % R2019b and earlier
    % Display this cropped, masked image.
    subplot(plotRows, plotRows, k);
    imshow(thisImage)
    baseFileName = sprintf('Image #%2.2d.png', k);
    fullFileName = fullfile(outputFolder, baseFileName);
    imwrite(thisImage, fullFileName);
end
msgbox('Done!');
%========================================================================================================
function [BW,maskedRGBImage] = createMask(RGB)
%createMask  Threshold RGB image using auto-generated code from colorThresholder app.
%  [BW,MASKEDRGBIMAGE] = createMask(RGB) thresholds image RGB using
%  auto-generated code from the colorThresholder app. The colorspace and
%  range for each channel of the colorspace were set within the app. The
%  segmentation mask is returned in BW, and a composite of the mask and
%  original RGB images is returned in maskedRGBImage.
% Auto-generated by colorThresholder app on 20-Dec-2021
%------------------------------------------------------
% Convert RGB image to chosen color space
I = rgb2hsv(RGB);
% Define thresholds for channel 1 based on histogram settings
channel1Min = 0.558;
channel1Max = 0.765;
% Define thresholds for channel 2 based on histogram settings
channel2Min = 0.251;
channel2Max = 1.000;
% Define thresholds for channel 3 based on histogram settings
channel3Min = 0.000;
channel3Max = 1.000;
% Create mask based on chosen histogram thresholds
sliderBW = (I(:,:,1) >= channel1Min ) & (I(:,:,1) <= channel1Max) & ...
    (I(:,:,2) >= channel2Min ) & (I(:,:,2) <= channel2Max) & ...
    (I(:,:,3) >= channel3Min ) & (I(:,:,3) <= channel3Max);
BW = sliderBW;
% Initialize output masked image based on input image.
maskedRGBImage = RGB;
% Set background pixels where BW is false to zero.
maskedRGBImage(repmat(~BW,[1 1 3])) = 0;
end