% Demo macro to very, very simple color detection in RGB color space.
% by ImageAnalyst
function SimpleColorDetection()
clc; % Clear command window.
clear; % Delete all variables.
close all; % Close all figure windows except those created by imtool.
% imtool close all; % Close all figure windows created by imtool.
workspace; % Make sure the workspace panel is showing.
% Change the current folder to the folder of this m-file.
% (The "cd" line of code below is from Brett Shoelson of The Mathworks.)
if(~isdeployed)
cd(fileparts(which(mfilename))); % From Brett
end
ver % Display user's toolboxes in their command window.
% Introduce the demo, and ask user if they want to continue or exit.
message = sprintf('This demo will illustrate very simple color detection in RGB color space.\nIt requires the Image Processing Toolbox.\nDo you wish to continue?');
reply = questdlg(message, 'Run Demo?', 'OK','Cancel', 'OK');
if strcmpi(reply, 'Cancel')
% User canceled so exit.
return;
end
try
% Check that user has the Image Processing Toolbox installed.
versionInfo = ver; % Capture their toolboxes in the variable.
hasIPT = false;
for k = 1:length(versionInfo)
if strcmpi(versionInfo(k).Name, 'Image Processing Toolbox') > 0
hasIPT = true;
end
end
if ~hasIPT
% User does not have the toolbox installed.
message = sprintf('Sorry, but you do not seem to have the Image Processing Toolbox.\nDo you want to try to continue anyway?');
reply = questdlg(message, 'Toolbox missing', 'Yes', 'No', 'Yes');
if strcmpi(reply, 'No')
% User said No, so exit.
return;
end
end
% Continue with the demo. Do some initialization stuff.
close all;
fontSize = 16;
figure;
% Maximize the figure.
set(gcf, 'Position', get(0, 'ScreenSize'));
% Change the current folder to the folder of this m-file.
% (The line of code below is from Brett Shoelson of The Mathworks.)
if(~isdeployed)
cd(fileparts(which(mfilename)));
end
% Ask user if they want to use a demo image or their own image.
message = sprintf('Do you want use a standard demo image,\nOr pick one of your own?');
reply2 = questdlg(message, 'Which Image?', 'Demo','My Own', 'Demo');
% Open an image.
if strcmpi(reply2, 'Demo')
% Read standard MATLAB demo image.
% fullImageFileName = 'peppers.png';
message = sprintf('Which demo image do you want to use?');
selectedImage = questdlg(message, 'Which Demo Image?', 'Onions', 'Peppers', 'Canoe', 'Onions');
if strcmp(selectedImage, 'Onions')
fullImageFileName = 'onion.png';
elseif strcmp(selectedImage, 'Peppers')
fullImageFileName = 'peppers.png';
else
fullImageFileName = 'canoe.tif';
end
else
% They want to pick their own.
% Change default directory to the one containing the standard demo images for the MATLAB Image Processing Toolbox.
originalFolder = pwd;
folder = 'C:\Program Files\MATLAB\R2010a\toolbox\images\imdemos';
if ~exist(folder, 'dir')
folder = pwd;
end
cd(folder);
% Browse for the image file.
[baseFileName, folder] = uigetfile('*.*', 'Specify an image file');
fullImageFileName = fullfile(folder, baseFileName);
% Set current folder back to the original one.
cd(originalFolder);
selectedImage = 'My own image'; % Need for the if threshold selection statement later.
end
% Check to see that the image exists. (Mainly to check on the demo images.)
if ~exist(fullImageFileName, 'file')
message = sprintf('This file does not exist:\n%s', fullImageFileName);
uiwait(msgbox(message));
return;
end
% Read in image into an array.
[rgbImage storedColorMap] = imread(fullImageFileName);
[rows columns numberOfColorBands] = size(rgbImage);
% If it's monochrome (indexed), convert it to color.
% Check to see if it's an 8-bit image needed later for scaling).
if strcmpi(class(rgbImage), 'uint8')
% Flag for 256 gray levels.
eightBit = true;
else
eightBit = false;
end
if numberOfColorBands == 1
if isempty(storedColorMap)
% Just a simple gray level image, not indexed with a stored color map.
% Create a 3D true color image where we copy the monochrome image into all 3 (R, G, & B) color planes.
rgbImage = cat(3, rgbImage, rgbImage, rgbImage);
else
% It's an indexed image.
rgbImage = ind2rgb(rgbImage, storedColorMap);
% ind2rgb() will convert it to double and normalize it to the range 0-1.
% Convert back to uint8 in the range 0-255, if needed.
if eightBit
rgbImage = uint8(255 * rgbImage);
end
end
end
% Display the original image.
subplot(3, 4, 1);
imshow(rgbImage);
drawnow; % Make it display immediately.
if numberOfColorBands > 1
title('Original Color Image', 'FontSize', fontSize);
else
caption = sprintf('Original Indexed Image\n(converted to true color with its stored colormap)');
title(caption, 'FontSize', fontSize);
end
% Extract out the color bands from the original image
% into 3 separate 2D arrays, one for each color component.
redBand = rgbImage(:, :, 1);
greenBand = rgbImage(:, :, 2);
blueBand = rgbImage(:, :, 3);
% Display them.
subplot(3, 4, 2);
imshow(redBand);
title('Red Band', 'FontSize', fontSize);
subplot(3, 4, 3);
imshow(greenBand);
title('Green Band', 'FontSize', fontSize);
subplot(3, 4, 4);
imshow(blueBand);
title('Blue Band', 'FontSize', fontSize);
message = sprintf('These are the individual color bands.\nNow we will compute the image histograms.');
reply = questdlg(message, 'Continue with Demo?', 'OK','Cancel', 'OK');
if strcmpi(reply, 'Cancel')
% User canceled so exit.
return;
end
fontSize = 13;
% Compute and plot the red histogram.
hR = subplot(3, 4, 6);
[countsR, grayLevelsR] = imhist(redBand);
maxGLValueR = find(countsR > 0, 1, 'last');
maxCountR = max(countsR);
bar(countsR, 'r');
grid on;
xlabel('Gray Levels');
ylabel('Pixel Count');
title('Histogram of Red Band', 'FontSize', fontSize);
% Compute and plot the green histogram.
hG = subplot(3, 4, 7);
[countsG, grayLevelsG] = imhist(greenBand);
maxGLValueG = find(countsG > 0, 1, 'last');
maxCountG = max(countsG);
bar(countsG, 'g', 'BarWidth', 0.95);
grid on;
xlabel('Gray Levels');
ylabel('Pixel Count');
title('Histogram of Green Band', 'FontSize', fontSize);
% Compute and plot the blue histogram.
hB = subplot(3, 4, 8);
[countsB, grayLevelsB] = imhist(blueBand);
maxGLValueB = find(countsB > 0, 1, 'last');
maxCountB = max(countsB);
bar(countsB, 'b');
grid on;
xlabel('Gray Levels');
ylabel('Pixel Count');
title('Histogram of Blue Band', 'FontSize', fontSize);
% Set all axes to be the same width and height.
% This makes it easier to compare them.
maxGL = max([maxGLValueR, maxGLValueG, maxGLValueB]);
if eightBit
maxGL = 255;
end
maxCount = max([maxCountR, maxCountG, maxCountB]);
axis([hR hG hB], [0 maxGL 0 maxCount]);
% Plot all 3 histograms in one plot.
subplot(3, 4, 5);
plot(grayLevelsR, countsR, 'r', 'LineWidth', 2);
grid on;
xlabel('Gray Levels');
ylabel('Pixel Count');
hold on;
plot(grayLevelsG, countsG, 'g', 'LineWidth', 2);
plot(grayLevelsB, countsB, 'b', 'LineWidth', 2);
title('Histogram of All Bands', 'FontSize', fontSize);
maxGrayLevel = max([maxGLValueR, maxGLValueG, maxGLValueB]);
% Trim x-axis to just the max gray level on the bright end.
if eightBit
xlim([0 255]);
else
xlim([0 maxGrayLevel]);
end
% Now select thresholds for the 3 color bands.
message = sprintf('Now we will select some color threshold ranges\nand display them over the histograms.');
reply = questdlg(message, 'Continue with Demo?', 'OK','Cancel', 'OK');
if strcmpi(reply, 'Cancel')
% User canceled so exit.
return;
end
% Assign the low and high thresholds for each color band.
if strcmpi(reply2, 'My Own') || strcmpi(selectedImage, 'Canoe') > 0
% Take a guess at the values that might work for the user's image.
redThresholdLow = graythresh(redBand);
redThresholdHigh = 255;
greenThresholdLow = 0;
greenThresholdHigh = graythresh(greenBand);
blueThresholdLow = 0;
blueThresholdHigh = graythresh(blueBand);
if eightBit
redThresholdLow = uint8(redThresholdLow * 255);
greenThresholdHigh = uint8(greenThresholdHigh * 255);
blueThresholdHigh = uint8(blueThresholdHigh * 255);
end
else
% Use values that I know work for the onions and peppers demo images.
redThresholdLow = 85;
redThresholdHigh = 255;
greenThresholdLow = 0;
greenThresholdHigh = 70;
blueThresholdLow = 0;
blueThresholdHigh = 90;
end
% Show the thresholds as vertical red bars on the histograms.
PlaceThresholdBars(6, redThresholdLow, redThresholdHigh);
PlaceThresholdBars(7, greenThresholdLow, greenThresholdHigh);
PlaceThresholdBars(8, blueThresholdLow, blueThresholdHigh);
message = sprintf('Now we will apply each color band threshold range to the color band.');
reply = questdlg(message, 'Continue with Demo?', 'OK','Cancel', 'OK');
if strcmpi(reply, 'Cancel')
% User canceled so exit.
return;
end
% Now apply each color band's particular thresholds to the color band
redMask = (redBand >= redThresholdLow) & (redBand <= redThresholdHigh);
greenMask = (greenBand >= greenThresholdLow) & (greenBand <= greenThresholdHigh);
blueMask = (blueBand >= blueThresholdLow) & (blueBand <= blueThresholdHigh);
% Display the thresholded binary images.
fontSize = 16;
subplot(3, 4, 10);
imshow(redMask, []);
title('Is-Red Mask', 'FontSize', fontSize);
subplot(3, 4, 11);
imshow(greenMask, []);
title('Is-Not-Green Mask', 'FontSize', fontSize);
subplot(3, 4, 12);
imshow(blueMask, []);
title('Is-Not-Blue Mask', 'FontSize', fontSize);
% Combine the masks to find where all 3 are "true."
% Then we will have the mask of only the red parts of the image.
redObjectsMask = uint8(redMask & greenMask & blueMask);
subplot(3, 4, 9);
imshow(redObjectsMask, []);
caption = sprintf('Mask of Only\nThe Red Objects');
title(caption, 'FontSize', fontSize);
% Tell user that we're going to filter out small objects.
smallestAcceptableArea = 100; % Keep areas only if they're bigger than this.
message = sprintf('Note the small regions in the image in the lower left.\nNext we will eliminate regions smaller than %d pixels.', smallestAcceptableArea);
reply = questdlg(message, 'Continue with Demo?', 'OK','Cancel', 'OK');
if strcmpi(reply, 'Cancel')
% User canceled so exit.
return;
end
% Open up a new figure, since the existing one is full.
figure;
% Maximize the figure.
set(gcf, 'Position', get(0, 'ScreenSize'));
% Get rid of small objects. Note: bwareaopen returns a logical.
redObjectsMask = uint8(bwareaopen(redObjectsMask, smallestAcceptableArea));
subplot(3, 3, 1);
imshow(redObjectsMask, []);
fontSize = 13;
caption = sprintf('bwareaopen() removed objects\nsmaller than %d pixels', smallestAcceptableArea);
title(caption, 'FontSize', fontSize);
% Smooth the border using a morphological closing operation, imclose().
structuringElement = strel('disk', 4);
redObjectsMask = imclose(redObjectsMask, structuringElement);
subplot(3, 3, 2);
imshow(redObjectsMask, []);
fontSize = 16;
title('Border smoothed', 'FontSize', fontSize);
% Fill in any holes in the regions, since they are most likely red also.
redObjectsMask = uint8(imfill(redObjectsMask, 'holes'));
subplot(3, 3, 3);
imshow(redObjectsMask, []);
title('Regions Filled', 'FontSize', fontSize);
message = sprintf('This is the filled, size-filtered mask.\nNow we will apply this mask to the original image.');
reply = questdlg(message, 'Continue with Demo?', 'OK','Cancel', 'OK');
if strcmpi(reply, 'Cancel')
% User canceled so exit.
return;
end
% You can only multiply integers if they are of the same type.
% (redObjectsMask is a logical array.)
% We need to convert the type of redObjectsMask to the same data type as redBand.
redObjectsMask = cast(redObjectsMask, class(redBand));
% Use the red object mask to mask out the red-only portions of the rgb image.
maskedImageR = redObjectsMask .* redBand;
maskedImageG = redObjectsMask .* greenBand;
maskedImageB = redObjectsMask .* blueBand;
% Show the masked off red image.
subplot(3, 3, 4);
imshow(maskedImageR);
title('Masked Red Image', 'FontSize', fontSize);
% Show the masked off green image.
subplot(3, 3, 5);
imshow(maskedImageG);
title('Masked Green Image', 'FontSize', fontSize);
% Show the masked off blue image.
subplot(3, 3, 6);
imshow(maskedImageB);
title('Masked Blue Image', 'FontSize', fontSize);
% Concatenate the masked color bands to form the rgb image.
maskedRGBImage = cat(3, maskedImageR, maskedImageG, maskedImageB);
% Show the masked off, original image.
subplot(3, 3, 8);
imshow(maskedRGBImage);
fontSize = 13;
caption = sprintf('Masked Original Image\nShowing Only the Red Objects');
title(caption, 'FontSize', fontSize);
% Show the original image next to it.
subplot(3, 3, 7);
imshow(rgbImage);
title('The Original Image (Again)', 'FontSize', fontSize);
% Measure the mean RGB and area of all the detected blobs.
[meanRGB, areas, numberOfBlobs] = MeasureBlobs(redObjectsMask, redBand, greenBand, blueBand);
if numberOfBlobs > 0
fprintf(1, '\n----------------------------------------------\n');
fprintf(1, 'Blob #, Area in Pixels, Mean R, Mean G, Mean B\n');
fprintf(1, '----------------------------------------------\n');
for blobNumber = 1 : numberOfBlobs
fprintf(1, '#%5d, %14d, %6.2f, %6.2f, %6.2f\n', blobNumber, areas(blobNumber), ...
meanRGB(blobNumber, 1), meanRGB(blobNumber, 2), meanRGB(blobNumber, 3));
end
else
% Alert user that no red blobs were found.
message = sprintf('No red blobs were found in the image:\n%s', fullImageFileName);
fprintf(1, '\n%s\n', message);
uiwait(msgbox(message));
end
subplot(3, 3, 9);
ShowCredits();
message = sprintf('Done!\n\nThe demo has finished.\n\nLook the MATLAB command window for\nthe area and color measurements of the %d regions.', numberOfBlobs);
msgbox(message);
catch ME
errorMessage = sprintf('Error running this m-file:\n%s\n\nThe error message is:\n%s', ...
mfilename('fullpath'), ME.message);
errordlg(errorMessage);
end
return; % from SimpleColorDetection()
% ---------- End of main function ---------------------------------
%----------------------------------------------------------------------------
% Measure the mean intensity and area of each blob in each color band.
function [meanRGB, areas, numberOfBlobs] = MeasureBlobs(maskImage, redBand, greenBand, blueBand)
[labeledImage numberOfBlobs] = bwlabel(maskImage, 8); % Label each blob so we can make measurements of it
if numberOfBlobs == 0
% Didn't detect any yellow blobs in this image.
meanRGB = [0 0 0];
areas = 0;
return;
end
% Get all the blob properties. Can only pass in originalImage in version R2008a and later.
blobMeasurementsR = regionprops(labeledImage, redBand, 'area', 'MeanIntensity');
blobMeasurementsG = regionprops(labeledImage, greenBand, 'area', 'MeanIntensity');
blobMeasurementsB = regionprops(labeledImage, blueBand, 'area', 'MeanIntensity');
meanRGB = zeros(numberOfBlobs, 3); % One row for each blob. One column for each color.
meanRGB(:,1) = [blobMeasurementsR.MeanIntensity]';
meanRGB(:,2) = [blobMeasurementsG.MeanIntensity]';
meanRGB(:,3) = [blobMeasurementsB.MeanIntensity]';
% If redBand etc. are double, the intensities will be in the range of 0-1.
% Multiply by 255 to get them back into the uint8 range of 0-255.
if ~strcmpi(class(redBand), 'uint8')
meanRGB = meanRGB * 255.0;
end
% Now assign the areas.
areas = zeros(numberOfBlobs, 3); % One row for each blob. One column for each color.
areas(:,1) = [blobMeasurementsR.Area]';
areas(:,2) = [blobMeasurementsG.Area]';
areas(:,3) = [blobMeasurementsB.Area]';
return; % from MeasureBlobs()
%----------------------------------------------------------------------------
% Function to show the low and high threshold bars on the histogram plots.
function PlaceThresholdBars(plotNumber, lowThresh, highThresh)
% Show the thresholds as vertical red bars on the histograms.
subplot(3, 4, plotNumber);
hold on;
maxYValue = ylim;
maxXValue = xlim;
hStemLines = stem([lowThresh highThresh], [maxYValue(2) maxYValue(2)], 'r');
children = get(hStemLines, 'children');
set(children(2),'visible', 'off');
% Place a text label on the bar chart showing the threshold.
fontSizeThresh = 14;
annotationTextL = sprintf('%d', lowThresh);
annotationTextH = sprintf('%d', highThresh);
% For text(), the x and y need to be of the data class "double" so let's cast both to double.
text(double(lowThresh + 5), double(0.85 * maxYValue(2)), annotationTextL, 'FontSize', fontSizeThresh, 'Color', [0 .5 0], 'FontWeight', 'Bold');
text(double(highThresh + 5), double(0.85 * maxYValue(2)), annotationTextH, 'FontSize', fontSizeThresh, 'Color', [0 .5 0], 'FontWeight', 'Bold');
% Show the range as arrows.
% Can't get it to work, with either gca or gcf.
% annotation(gca, 'arrow', [lowThresh/maxXValue(2) highThresh/maxXValue(2)],[0.7 0.7]);
return; % from PlaceThresholdBars()
%----------------------------------------------------------------------------
% Display the MATLAB logo.
function ShowCredits()
% xpklein;
% surf(peaks(30));
logoFig = subplot(3,3,9);
caption = sprintf('A MATLAB Demo\nby ImageAnalyst');
text(0.5,1.15, caption, 'Color','r', 'FontSize', 18, 'FontWeight','b', 'HorizontalAlignment', 'Center') ;
positionOfLowerRightPlot = get(logoFig, 'position');
L = 40*membrane(1,25);
logoax = axes('CameraPosition', [-193.4013 -265.1546 220.4819],...
'CameraTarget',[26 26 10], ...
'CameraUpVector',[0 0 1], ...
'CameraViewAngle',9.5, ...
'DataAspectRatio', [1 1 .9],...
'Position', positionOfLowerRightPlot, ...
'Visible','off', ...
'XLim',[1 51], ...
'YLim',[1 51], ...
'ZLim',[-13 40], ...
'parent',gcf);
s = surface(L, ...
'EdgeColor','none', ...
'FaceColor',[0.9 0.2 0.2], ...
'FaceLighting','phong', ...
'AmbientStrength',0.3, ...
'DiffuseStrength',0.6, ...
'Clipping','off',...
'BackFaceLighting','lit', ...
'SpecularStrength',1.1, ...
'SpecularColorReflectance',1, ...
'SpecularExponent',7, ...
'Tag','TheMathWorksLogo', ...
'parent',logoax);
l1 = light('Position',[40 100 20], ...
'Style','local', ...
'Color',[0 0.8 0.8], ...
'parent',logoax);
l2 = light('Position',[.5 -1 .4], ...
'Color',[0.8 0.8 0], ...
'parent',logoax);
return; % from ShowCredits()
