Please update me how I can detect two colors by applying thresholds simultaneously . I am interested in Green and Red.how to do the manual calculation

% Demo macro to very, very simple color detection in % HSV (Hue, Saturation, Value) color space. % Requires the Image Processing Toolbox. Developed under MATLAB R2014a. % function SimpleColorDetectionByHue() 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\nin HSV 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. hasIPT = license('test', 'image_toolbox'); 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, 'units','normalized','outerposition',[0 0 1 1]);

% 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', 'Kids', 'Onions'); if strcmp(selectedImage, 'Onions') fullImageFileName = 'onion.png'; elseif strcmp(selectedImage, 'Peppers') fullImageFileName = 'peppers.png'; else fullImageFileName = 'kids.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); hRGB = imshow(rgbImage); % Set up an infor panel so you can mouse around and inspect the value values. hrgbPI = impixelinfo(hRGB); set(hrgbPI, 'Units', 'Normalized', 'Position',[.15 .69 .15 .02]); 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

% Convert RGB image to HSV hsvImage = rgb2hsv(rgbImage); % Extract out the H, S, and V images individually hImage = hsvImage(:,:,1); sImage = hsvImage(:,:,2); vImage = hsvImage(:,:,3); % Display the hue image. subplot(3, 4, 2); h1 = imshow(hImage); title('Hue Image', 'FontSize', fontSize); % Set up an infor panel so you can mouse around and inspect the hue values. hHuePI = impixelinfo(h1); set(hHuePI, 'Units', 'Normalized', 'Position',[.34 .69 .15 .02]); % Display the saturation image. h2 = subplot(3, 4, 3); imshow(sImage); title('Saturation Image', 'FontSize', fontSize); % Set up an infor panel so you can mouse around and inspect the saturation values. hSatPI = impixelinfo(h2); set(hSatPI, 'Units', 'Normalized', 'Position',[.54 .69 .15 .02]); % Display the value image. h3 = subplot(3, 4, 4); imshow(vImage); title('Value Image', 'FontSize', fontSize); % Set up an infor panel so you can mouse around and inspect the value values. hValuePI = impixelinfo(h3); set(hValuePI, 'Units', 'Normalized', 'Position',[.75 .69 .15 .02]);

message = sprintf('These are the individual HSV 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

% Compute and plot the histogram of the "hue" band. hHuePlot = subplot(3, 4, 6); [hueCounts, hueBinValues] = imhist(hImage); maxHueBinValue = find(hueCounts > 0, 1, 'last'); maxCountHue = max(hueCounts); % Display with area() rather than bar, due to bug in bar(). The bug, and workaround of using area(), are discussed in % http://www.mathworks.com/matlabcentral/answers/103538-why-does-a-bar-subplot-change-when-i-create-another-bar-subplot-on-the-same-figure-in-matlab-8-0-r % Supposedly it's been fixed in R2014b. % bar(hueBinValues, hueCounts, 'r'); area(hueBinValues, hueCounts, 'FaceColor', 'r'); grid on; xlabel('Hue Value'); ylabel('Pixel Count'); title('Histogram of Hue Image', 'FontSize', fontSize);

% Compute and plot the histogram of the "saturation" band. hSaturationPlot = subplot(3, 4, 7); [saturationCounts, saturationBinValues] = imhist(sImage); maxSaturationBinValue = find(saturationCounts > 0, 1, 'last'); maxCountSaturation = max(saturationCounts); % bar(saturationBinValues, saturationCounts, 'g', 'BarWidth', 0.95); area(saturationBinValues, saturationCounts, 'FaceColor', 'g'); grid on; xlabel('Saturation Value'); ylabel('Pixel Count'); title('Histogram of Saturation Image', 'FontSize', fontSize);

% Compute and plot the histogram of the "value" band. hValuePlot = subplot(3, 4, 8); [valueCounts, valueBinValues] = imhist(vImage); maxValueBinValue = find(valueCounts > 0, 1, 'last'); maxCountValue = max(valueCounts); % bar(valueBinValues, valueCounts, 'b'); area(valueBinValues, valueCounts, 'FaceColor', 'b'); grid on; xlabel('Value Value'); ylabel('Pixel Count'); title('Histogram of Value Image', 'FontSize', fontSize);

% Set all axes to be the same width and height. % This makes it easier to compare them. maxCount = max([maxCountHue, maxCountSaturation, maxCountValue]); axis([hHuePlot hSaturationPlot hValuePlot], [0 1 0 maxCount]);

% Plot all 3 histograms in one plot. subplot(3, 4, 5); plot(hueBinValues, hueCounts, 'r', 'LineWidth', 2); grid on; xlabel('Values'); ylabel('Pixel Count'); hold on; plot(saturationBinValues, saturationCounts, 'g', 'LineWidth', 2); plot(valueBinValues, valueCounts, 'b', 'LineWidth', 2); title('Histogram of All Bands', 'FontSize', fontSize); maxGrayLevel = max([maxHueBinValue, maxSaturationBinValue, maxValueBinValue]); % Just for our information.... % Make x-axis to just the max gray level on the bright end. xlim([0 1]);

% 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, 'Kids') > 0 % Take a guess at the values that might work for the user's image. hueThresholdLow = 0; hueThresholdHigh = graythresh(hImage); saturationThresholdLow = graythresh(sImage); saturationThresholdHigh = 1.0; valueThresholdLow = graythresh(vImage); valueThresholdHigh = 1.0; else % Use values that I know work for the onions and peppers demo images. [hueThresholdLow, hueThresholdHigh, saturationThresholdLow, saturationThresholdHigh, valueThresholdLow, valueThresholdHigh] = SetThresholds() end % Interactively and visually set/adjust thresholds using custom thresholding application. % Available on the File Exchange: http://www.mathworks.com/matlabcentral/fileexchange/29372-thresholding-an-image % [hueThresholdLow, hueThresholdHigh] = threshold(hueThresholdLow, hueThresholdHigh, hImage); % [saturationThresholdLow, saturationThresholdHigh] = threshold(saturationThresholdLow, saturationThresholdHigh, sImage); % [valueThresholdLow, valueThresholdHigh] = threshold(valueThresholdLow, valueThresholdHigh, vImage);

% Show the thresholds as vertical magenta bars on the histograms. PlaceThresholdBars(6, hueThresholdLow, hueThresholdHigh); PlaceThresholdBars(7, saturationThresholdLow, saturationThresholdHigh); PlaceThresholdBars(8, valueThresholdLow, valueThresholdHigh);

message = sprintf('Next we will apply each color band threshold range to its respective 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 hueMask = (hImage >= hueThresholdLow) & (hImage <= hueThresholdHigh); saturationMask = (sImage >= saturationThresholdLow) & (sImage <= saturationThresholdHigh); valueMask = (vImage >= valueThresholdLow) & (vImage <= valueThresholdHigh);

% Display the thresholded binary images. fontSize = 16; subplot(3, 4, 10); imshow(hueMask, []); title('= Hue Mask', 'FontSize', fontSize); subplot(3, 4, 11); imshow(saturationMask, []); title('& Saturation Mask', 'FontSize', fontSize); subplot(3, 4, 12); imshow(valueMask, []); title('& Value 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. coloredObjectsMask = uint8(hueMask & saturationMask & valueMask); subplot(3, 4, 9); imshow(coloredObjectsMask, []); caption = sprintf('Mask of Only Regions\nof The Specified Color'); 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, 'units','normalized','outerposition',[0 0 1 1]);

% Get rid of small objects. Note: bwareaopen returns a logical. coloredObjectsMask = uint8(bwareaopen(coloredObjectsMask, smallestAcceptableArea)); subplot(3, 3, 1); imshow(coloredObjectsMask, []); 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); coloredObjectsMask = imclose(coloredObjectsMask, structuringElement); subplot(3, 3, 2); imshow(coloredObjectsMask, []); fontSize = 16; title('Border smoothed', 'FontSize', fontSize);

% Fill in any holes in the regions, since they are most likely red also. coloredObjectsMask = imfill(logical(coloredObjectsMask), 'holes'); subplot(3, 3, 3); imshow(coloredObjectsMask, []); title('Regions Filled', 'FontSize', fontSize);

message = sprintf('This is the filled, size-filtered mask.\nNext we will apply this mask to the original RGB 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. % (coloredObjectsMask is a logical array.) % We need to convert the type of coloredObjectsMask to the same data type as hImage. coloredObjectsMask = cast(coloredObjectsMask, 'like', rgbImage); % coloredObjectsMask = cast(coloredObjectsMask, class(rgbImage));

% Use the colored object mask to mask out the colored-only portions of the rgb image. maskedImageR = coloredObjectsMask .* rgbImage(:,:,1); maskedImageG = coloredObjectsMask .* rgbImage(:,:,2); maskedImageB = coloredObjectsMask .* rgbImage(:,:,3); % Show the masked off red image. subplot(3, 3, 4); imshow(maskedImageR); title('Masked Red Image', 'FontSize', fontSize); % Show the masked off saturation image. subplot(3, 3, 5); imshow(maskedImageG); title('Masked Green Image', 'FontSize', fontSize); % Show the masked off value 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 Regions of Only the Specified Color'); 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 HSV and area of all the detected blobs. [meanHSV, areas, numberOfBlobs] = MeasureBlobs(coloredObjectsMask, hImage, sImage, vImage); if numberOfBlobs > 0 fprintf(1, '\n----------------------------------------------\n'); fprintf(1, 'Blob #, Area in Pixels, Mean H, Mean S, Mean V\n'); fprintf(1, '----------------------------------------------\n'); for blobNumber = 1 : numberOfBlobs fprintf(1, '#%5d, %14d, %6.2f, %6.2f, %6.2f\n', blobNumber, areas(blobNumber), ... meanHSV(blobNumber, 1), meanHSV(blobNumber, 2), meanHSV(blobNumber, 3)); end else % Alert user that no colored blobs were found. message = sprintf('No blobs of the specified color 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); uiwait(msgbox(message)); catch ME errorMessage = sprintf('Error in function %s() at line %d.\n\nError Message:\n%s', ... ME.stack(1).name, ME.stack(1).line, ME.message); fprintf(1, '%s\n', errorMessage); uiwait(warndlg(errorMessage)); end return; % from SimpleColorDetection() % ---------- End of main function ---------------------------------

%---------------------------------------------------------------------------- function [meanHSV, areas, numberOfBlobs] = MeasureBlobs(maskImage, hImage, sImage, vImage) try [labeledImage, numberOfBlobs] = bwlabel(maskImage, 8); % Label each blob so we can make measurements of it if numberOfBlobs == 0 % Didn't detect any blobs of the specified color in this image. meanHSV = [0 0 0]; areas = 0; return; end % Get all the blob properties. Can only pass in originalImage in version R2008a and later. blobMeasurementsHue = regionprops(labeledImage, hImage, 'area', 'MeanIntensity'); blobMeasurementsSat = regionprops(labeledImage, sImage, 'area', 'MeanIntensity'); blobMeasurementsValue = regionprops(labeledImage, vImage, 'area', 'MeanIntensity'); meanHSV = zeros(numberOfBlobs, 3); % One row for each blob. One column for each color. meanHSV(:,1) = [blobMeasurementsHue.MeanIntensity]'; meanHSV(:,2) = [blobMeasurementsSat.MeanIntensity]'; meanHSV(:,3) = [blobMeasurementsValue.MeanIntensity]'; % Now assign the areas. areas = zeros(numberOfBlobs, 3); % One row for each blob. One column for each color. areas(:,1) = [blobMeasurementsHue.Area]'; areas(:,2) = [blobMeasurementsSat.Area]'; areas(:,3) = [blobMeasurementsValue.Area]'; catch ME errorMessage = sprintf('Error in function %s() at line %d.\n\nError Message:\n%s', ... ME.stack(1).name, ME.stack(1).line, ME.message); fprintf(1, '%s\n', errorMessage); uiwait(warndlg(errorMessage)); end return; % from MeasureBlobs() %---------------------------------------------------------------------------- % Function to show the low and high threshold bars on the histogram plots. function PlaceThresholdBars(plotNumber, lowThresh, highThresh) try % Show the thresholds as vertical red bars on the histograms. subplot(3, 4, plotNumber); hold on; yLimits = ylim; line([lowThresh, lowThresh], yLimits, 'Color', 'r', 'LineWidth', 3); line([highThresh, highThresh], yLimits, 'Color', 'r', 'LineWidth', 3); % 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 * yLimits(2)), annotationTextL, 'FontSize', fontSizeThresh, 'Color', [0 .5 0], 'FontWeight', 'Bold'); text(double(highThresh + 5), double(0.85 * yLimits(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]);

catch ME errorMessage = sprintf('Error in function %s() at line %d.\n\nError Message:\n%s', ... ME.stack(1).name, ME.stack(1).line, ME.message); fprintf(1, '%s\n', errorMessage); uiwait(warndlg(errorMessage)); end return; % from PlaceThresholdBars()

%--------------------------------------------------------------------------------------------------------------------------------- % Ask user what color they want for the onions and peppers images and set up pre-defined threshold values. function [hueThresholdLow, hueThresholdHigh, saturationThresholdLow, saturationThresholdHigh, valueThresholdLow, valueThresholdHigh] = SetThresholds() try % button = menu('What color do you want to find?', 'yellow', 'green', 'red', 'white'); % Menu with purple commented out because it's all around and the regionfill just ends up selecting the whole image. button = menu('What color do you want to find?', 'yellow', 'green', 'red', 'white', 'purple'); % Use values that I know work for the onions and peppers demo images. switch button case 1 % Yellow hueThresholdLow = 0.10; hueThresholdHigh = 0.14; saturationThresholdLow = 0.4; saturationThresholdHigh = 1; valueThresholdLow = 0.8; valueThresholdHigh = 1.0; case 2 % Green hueThresholdLow = 0.15; hueThresholdHigh = 0.60; saturationThresholdLow = 0.36; saturationThresholdHigh = 1; valueThresholdLow = 0; valueThresholdHigh = 0.8; case 3 % Red. % IMPORTANT NOTE FOR RED. Red spans hues both less than 0.1 and more than 0.8. % We're only getting one range here so we will miss some of the red pixels - those with hue less than around 0.1. % To properly get all reds, you'd have to get a hue mask that is the result of TWO threshold operations. hueThresholdLow = 0.80; hueThresholdHigh = 1; saturationThresholdLow = 0.58; saturationThresholdHigh = 1; valueThresholdLow = 0.55; valueThresholdHigh = 1.0; case 4 % White hueThresholdLow = 0.0; hueThresholdHigh = 1; saturationThresholdLow = 0; saturationThresholdHigh = 0.36; valueThresholdLow = 0.7; valueThresholdHigh = 1.0; otherwise % Purple hueThresholdLow = 0.76; hueThresholdHigh = 0.94; saturationThresholdLow = 0.33; saturationThresholdHigh = 0.67; valueThresholdLow = 0.1; valueThresholdHigh = 0.7; end catch ME errorMessage = sprintf('Error in function %s() at line %d.\n\nError Message:\n%s', ... ME.stack(1).name, ME.stack(1).line, ME.message); fprintf(1, '%s\n', errorMessage); uiwait(warndlg(errorMessage)); end return; % From SetThresholds()

%--------------------------------------------------------------------------------------------------------------------------------- % Display the MATLAB logo. function ShowCredits() try % xpklein; % surf(peaks(30)); logoFig = subplot(3,3,9); caption = sprintf('A MATLAB Demo'); 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',1.0, ... '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); catch ME errorMessage = sprintf('Error in function %s() at line %d.\n\nError Message:\n%s', ... ME.stack(1).name, ME.stack(1).line, ME.message); fprintf(1, '%s\n', errorMessage); uiwait(warndlg(errorMessage)); end return; % from ShowCredits()

Answer 1

[Image Analyst]

You have to do each color one at a time, then combine them if you want a mask that includes both.