I want to find out the greeness of an image , but iam not getting the output for the code which you have provided

% 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()

[Rik]

This is quite difficult to read. To me it is not clear what exactly is your question. What errors are you getting? What data did you put in? What output are you expecting?