Color detection [Matlab]

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From: ImageAnalyst on 3 Aug 2010 07:33

On Aug 3, 7:16 am, "Kenny Nam" <kennynam...(a)hotmail.com> wrote:
> I just met with my supervisor.He asked to filtered the yellow object from a picture first,then only compare the yellowish with the data storage.The ratio of Yellow in RGB is G>R>B....Thanks for the help.

-------------------------------------
OK - sounds easy enough (although with that definition you'll also get
green objects unless you use some weights).
Good luck.

From: Kenny Nam on 3 Aug 2010 18:15

ImageAnalyst <imageanalyst(a)mailinator.com> wrote in message <81b160f5-fdb0-4c4e-b221-d2ab8409bd57(a)i24g2000yqa.googlegroups.com>...
> On Aug 3, 7:16 am, "Kenny Nam" <kennynam...(a)hotmail.com> wrote:
> > I just met with my supervisor.He asked to filtered the yellow object from a picture first,then only compare the yellowish with the data storage.The ratio of Yellow in RGB is G>R>B....Thanks for the help.
>
> -------------------------------------
> OK - sounds easy enough (although with that definition you'll also get
> green objects unless you use some weights).
> Good luck.

First of all,i have to apologize for my stupid and noob questions,cause i just can study matlab from internet and file exchange from matlab to further my tasks in my final year project,tats make me stress and headache.For the part of filtering,i just able to find the file did it in manually mean we have to crop the certain part for analyst but i have to do a programme to crop the certain color (yellow) automaticlly and filter the another color in the picture,It is to make sure the background of the picture wont affect my analyst of percentage in yellow.Can you send me the link related to my situation,i will try to study and use to it?Thanks for your help once again.

From: ImageAnalyst on 3 Aug 2010 18:45

Kenny Nam:
OK, I found some new thresholds that work with the yellow pepper in
the standard MATLAB demo image, and I've modified my demo to pick out
the yellow objects and give the "percent area." You just need to
adapt it to your images - find thresholds that work for your
particular images. The values will be somewhat similar to the ones I
use.
-Image Analyst

Be sure to join any lines the newsreader split into two!!!

% 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

% 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?');
reply = questdlg(message, 'Which Image?', 'Demo','My Own', 'Demo');
% Open an image.
if strcmpi(reply, '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);
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
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
% 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 strcmp(reply, 'My Own') || strcmp(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 red objects in the onions and
peppers demo images.
redThresholdLow = 85;
redThresholdHigh = 255;
greenThresholdLow = 0;
greenThresholdHigh = 70;
blueThresholdLow = 0;
blueThresholdHigh = 90;
% Use values that I know work for yellow objects in the onions and
peppers demo images.
redThresholdLow = 219;
redThresholdHigh = 255;
greenThresholdLow = 150;
greenThresholdHigh = 242;
blueThresholdLow = 0;
blueThresholdHigh = 16;
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 Yellow parts of the image.
redObjectsMask = uint8(redMask & greenMask & blueMask);
subplot(3, 4, 9);
imshow(redObjectsMask, []);
caption = sprintf('Mask of Only\nThe Yellow 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.
strDataType = class(redBand);
redObjectsMask = eval([strDataType '(redObjectsMask)']);

% 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 Yellow
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);

% Get area fraction
areaFraction = areas / (double(rows) * double(columns));
percentArea = areaFraction * 100.0;

fprintf(1, '\n----------------------------------------------\n');
fprintf(1, 'Blob #, Area in Pixels, Pct. Area, Mean R, Mean G, Mean B
\n');
fprintf(1, '----------------------------------------------\n');
for blobNumber = 1 : numberOfBlobs
fprintf(1, '#%5d, %14d, %6.2f, %6.2f, %6.2f, %6.2f\n',
blobNumber, areas(blobNumber), ...
percentArea(blobNumber), meanRGB(blobNumber, 1), meanRGB(blobNumber,
2), meanRGB(blobNumber, 3));
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);
% ---------- End of main function ---------------------------------

%----------------------------------------------------------------------------
function [meanRGB, areas, numberOfBlobs] = MeasureBlobs(maskImage,
redBand, greenBand, blueBand)
[labeledImage numberOfBlobs] = bwlabel(maskImage, 8); % Label
each blob so we can make measurements of it
% 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: Kenny Nam on 4 Aug 2010 02:49

ImageAnalyst <imageanalyst(a)mailinator.com> wrote in message <73ba4c6d-23fd-4a6e-8842-044d22994c6a(a)z10g2000yqb.googlegroups.com>...
> Kenny Nam:
> OK, I found some new thresholds that work with the yellow pepper in
> the standard MATLAB demo image, and I've modified my demo to pick out
> the yellow objects and give the "percent area." You just need to
> adapt it to your images - find thresholds that work for your
> particular images. The values will be somewhat similar to the ones I
> use.
> -Image Analyst
>
> Be sure to join any lines the newsreader split into two!!!
>
> % 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
>
> % 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?');
> reply = questdlg(message, 'Which Image?', 'Demo','My Own', 'Demo');
> % Open an image.
> if strcmpi(reply, '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);
> 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
> 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
> % 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 strcmp(reply, 'My Own') || strcmp(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 red objects in the onions and
> peppers demo images.
> redThresholdLow = 85;
> redThresholdHigh = 255;
> greenThresholdLow = 0;
> greenThresholdHigh = 70;
> blueThresholdLow = 0;
> blueThresholdHigh = 90;
> % Use values that I know work for yellow objects in the onions and
> peppers demo images.
> redThresholdLow = 219;
> redThresholdHigh = 255;
> greenThresholdLow = 150;
> greenThresholdHigh = 242;
> blueThresholdLow = 0;
> blueThresholdHigh = 16;
> 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 Yellow parts of the image.
> redObjectsMask = uint8(redMask & greenMask & blueMask);
> subplot(3, 4, 9);
> imshow(redObjectsMask, []);
> caption = sprintf('Mask of Only\nThe Yellow 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.
> strDataType = class(redBand);
> redObjectsMask = eval([strDataType '(redObjectsMask)']);
>
> % 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 Yellow
> 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);
>
> % Get area fraction
> areaFraction = areas / (double(rows) * double(columns));
> percentArea = areaFraction * 100.0;
>
> fprintf(1, '\n----------------------------------------------\n');
> fprintf(1, 'Blob #, Area in Pixels, Pct. Area, Mean R, Mean G, Mean B
> \n');
> fprintf(1, '----------------------------------------------\n');
> for blobNumber = 1 : numberOfBlobs
> fprintf(1, '#%5d, %14d, %6.2f, %6.2f, %6.2f, %6.2f\n',
> blobNumber, areas(blobNumber), ...
> percentArea(blobNumber), meanRGB(blobNumber, 1), meanRGB(blobNumber,
> 2), meanRGB(blobNumber, 3));
> 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);
> % ---------- End of main function ---------------------------------
>
>
> %----------------------------------------------------------------------------
> function [meanRGB, areas, numberOfBlobs] = MeasureBlobs(maskImage,
> redBand, greenBand, blueBand)
> [labeledImage numberOfBlobs] = bwlabel(maskImage, 8); % Label
> each blob so we can make measurements of it
> % 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;

Thanks for you guide.I have tried the coding bt it unable to pick the yellow from the image(Filtering) and can't run my own picture as well.It just able to run the demo.Sorry for disturbing you once again.

From: Kenny Nam on 4 Aug 2010 03:17

"Kenny Nam" <kennynam517(a)hotmail.com> wrote in message <i3b2hb$pif$1(a)fred.mathworks.com>...
> ImageAnalyst <imageanalyst(a)mailinator.com> wrote in message <73ba4c6d-23fd-4a6e-8842-044d22994c6a(a)z10g2000yqb.googlegroups.com>...
> > Kenny Nam:
> > OK, I found some new thresholds that work with the yellow pepper in
> > the standard MATLAB demo image, and I've modified my demo to pick out
> > the yellow objects and give the "percent area." You just need to
> > adapt it to your images - find thresholds that work for your
> > particular images. The values will be somewhat similar to the ones I
> > use.
> > -Image Analyst
> >
> > Be sure to join any lines the newsreader split into two!!!
> >
> > % 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
> >
> > % 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?');
> > reply = questdlg(message, 'Which Image?', 'Demo','My Own', 'Demo');
> > % Open an image.
> > if strcmpi(reply, '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);
> > 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
> > 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
> > % 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 strcmp(reply, 'My Own') || strcmp(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 red objects in the onions and
> > peppers demo images.
> > redThresholdLow = 85;
> > redThresholdHigh = 255;
> > greenThresholdLow = 0;
> > greenThresholdHigh = 70;
> > blueThresholdLow = 0;
> > blueThresholdHigh = 90;
> > % Use values that I know work for yellow objects in the onions and
> > peppers demo images.
> > redThresholdLow = 219;
> > redThresholdHigh = 255;
> > greenThresholdLow = 150;
> > greenThresholdHigh = 242;
> > blueThresholdLow = 0;
> > blueThresholdHigh = 16;
> > 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 Yellow parts of the image.
> > redObjectsMask = uint8(redMask & greenMask & blueMask);
> > subplot(3, 4, 9);
> > imshow(redObjectsMask, []);
> > caption = sprintf('Mask of Only\nThe Yellow 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.
> > strDataType = class(redBand);
> > redObjectsMask = eval([strDataType '(redObjectsMask)']);
> >
> > % 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 Yellow
> > 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);
> >
> > % Get area fraction
> > areaFraction = areas / (double(rows) * double(columns));
> > percentArea = areaFraction * 100.0;
> >
> > fprintf(1, '\n----------------------------------------------\n');
> > fprintf(1, 'Blob #, Area in Pixels, Pct. Area, Mean R, Mean G, Mean B
> > \n');
> > fprintf(1, '----------------------------------------------\n');
> > for blobNumber = 1 : numberOfBlobs
> > fprintf(1, '#%5d, %14d, %6.2f, %6.2f, %6.2f, %6.2f\n',
> > blobNumber, areas(blobNumber), ...
> > percentArea(blobNumber), meanRGB(blobNumber, 1), meanRGB(blobNumber,
> > 2), meanRGB(blobNumber, 3));
> > 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);
> > % ---------- End of main function ---------------------------------
> >
> >
> > %----------------------------------------------------------------------------
> > function [meanRGB, areas, numberOfBlobs] = MeasureBlobs(maskImage,
> > redBand, greenBand, blueBand)
> > [labeledImage numberOfBlobs] = bwlabel(maskImage, 8); % Label
> > each blob so we can make measurements of it
> > % 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;
>
> Thanks for you guide.I have tried the coding bt it unable to pick the yellow from the image(Filtering) and can't run my own picture as well.It just able to run the demo.Sorry for disturbing you once again.

% 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

% 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?');
reply = questdlg(message, 'Which Image?', 'Demo','My Own', 'Demo');
% Open an image.
if strcmpi(reply, '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\R2009b\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);
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
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
% 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 strcmp(reply, 'My Own') || strcmp(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.
strDataType = class(redBand);
redObjectsMask = eval([strDataType '(redObjectsMask)']);

% 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);
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

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);
% ---------- End of main function ---------------------------------

%----------------------------------------------------------------------------
function [meanRGB, areas, numberOfBlobs] = MeasureBlobs(maskImage, redBand, greenBand, blueBand)
[labeledImage numberOfBlobs] = bwlabel(maskImage, 8); % Label each blob so we can make measurements of it
% 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;

This coding is based on RGB and after plot the histrogram,it able to filter the another colors and just show RED at the last. Can you teach me how to filter the another colors and just show the yellow color then only go for the histogram based on the yellow in RGB,i have tried to modify by my own,bt plenty of errors.million of thanks for your advice and help first....

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