اطلاعیه

**tavajo9** · 2015-07-17T15:30:36

پاسخ : detect color wavelet image

لطفا اگه میشه من راهنمایی کنید :cry: :cry2:

**tavajo9** · 2015-07-18T01:35:26

پاسخ : detect color wavelet image

یعنی هیچکی بلد نیس

اینم یه نمونه برنامه

لطفا عجله کنید

% HSV (Hue, Saturation, Value) color space.
% Requires the Image Processing Toolbox. Developed under MATLAB R2010a.
% by ImageAnalyst
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 yellow color detection\nin HSV color space.\nIt requires the Image Processing Toolbox.\nDo you wish to continue?&#039

;
reply = questdlg(message, 'Run Demo?', 'OK','Cancel', 'OK&#039

;
if strcmpi(reply, 'Cancel&#039

% User canceled so exit.
return;
end

try
% Check that user has the Image Processing Toolbox installed.
versionInfo = ver; % Capture their toolboxes in the variable.
hasIPT = false;
for k = 1:length(versionInfo)
if strcmpi(versionInfo(k).Name, 'Image Processing Toolbox&#039

> 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?&#039

;
reply = questdlg(message, 'Toolbox missing', 'Yes', 'No', 'Yes&#039

;
if strcmpi(reply, 'No&#039

% 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&#039

);

% 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?&#039

;
reply2 = questdlg(message, 'Which Image?', 'Demo','My Own', 'Demo&#039

;
% Open an image.
if strcmpi(reply2, 'Demo&#039

% Read standard MATLAB demo image.
% fullImageFileName = 'peppers.png';
message = sprintf('Which demo image do you want to use?&#039

;
selectedImage = questdlg(message, 'Which Demo Image?', 'Onions', 'Peppers', 'Kids', 'Onions&#039

;
if strcmp(selectedImage, 'Onions&#039

fullImageFileName = 'onion.png';
elseif strcmp(selectedImage, 'Peppers&#039

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&#039

folder = pwd;
end
cd(folder);
% Browse for the image file.
[baseFileName, folder] = uigetfile('*.*', 'Specify an image file&#039

;
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&#039

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&#039

% Flag for 256 gray levels.
eightBit = true;
else
eightBit = false;
end
if numberOfColorBands == 1
if isempty(storedColorMap)
% Just a simple gray level image, not indexed with a stored color map.
% Create a 3D true color image where we copy the monochrome image into all 3 (R, G, & B) color planes.
rgbImage = cat(3, rgbImage, rgbImage, rgbImage);
else
% It's an indexed image.
rgbImage = ind2rgb(rgbImage, storedColorMap);
% ind2rgb() will convert it to double and normalize it to the range 0-1.
% Convert back to uint8 in the range 0-255, if needed.
if eightBit
rgbImage = uint8(255 * rgbImage);
end
end
end

% Display the original image.
subplot(3, 4, 1);
imshow(rgbImage);
drawnow; % Make it display immediately.
if numberOfColorBands > 1
title('Original Color Image', 'FontSize', fontSize);
else
caption = sprintf('Original Indexed Image\n(converted to true color with its stored colormap)&#039

;
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 them.
subplot(3, 4, 2);
imshow(hImage);
title('Hue Image', 'FontSize', fontSize);
subplot(3, 4, 3);
imshow(sImage);
title('Saturation Image', 'FontSize', fontSize);
subplot(3, 4, 4);
imshow(vImage);
title('Value Image', 'FontSize', fontSize);
message = sprintf('These are the individual HSV color bands.\nNow we will compute the image histograms.&#039

;
reply = questdlg(message, 'Continue with Demo?', 'OK','Cancel', 'OK&#039

;
if strcmpi(reply, 'Cancel&#039

% 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&#039

;
maxCountHue = max(hueCounts);
bar(hueBinValues, hueCounts, 'r&#039

;
grid on;
xlabel('Hue Value&#039

;
ylabel('Pixel Count&#039

;
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&#039

;
maxCountSaturation = max(saturationCounts);
bar(saturationBinValues, saturationCounts, 'g', 'BarWidth', 0.95);
grid on;
xlabel('Saturation Value&#039

;
ylabel('Pixel Count&#039

;
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&#039

;
maxCountValue = max(valueCounts);
bar(valueBinValues, valueCounts, 'b&#039

;
grid on;
xlabel('Value Value&#039

;
ylabel('Pixel Count&#039

;
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&#039

;
ylabel('Pixel Count&#039

;
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]);
% 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.&#039

;
reply = questdlg(message, 'Continue with Demo?', 'OK','Cancel', 'OK&#039

;
if strcmpi(reply, 'Cancel&#039

% User canceled so exit.
return;
end

% Assign the low and high thresholds for each color band.
if strcmpi(reply2, 'My Own&#039

|| strcmpi(selectedImage, 'Kids&#039

> 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 = 0.10;
hueThresholdHigh = 0.14;
saturationThresholdLow = 0.4;
saturationThresholdHigh = 1;
valueThresholdLow = 0.8;
valueThresholdHigh = 1.0;
end

% Show the thresholds as vertical red 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.&#039

;
reply = questdlg(message, 'Continue with Demo?', 'OK','Cancel', 'OK&#039

;
if strcmpi(reply, 'Cancel&#039

% 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.
yellowObjectsMask = uint8(hueMask & saturationMask & valueMask);
subplot(3, 4, 9);
imshow(yellowObjectsMask, []);
caption = sprintf('Mask of Only\nThe Yellow Objects&#039

;
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&#039

;
if strcmpi(reply, 'Cancel&#039

% 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&#039

);

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

% Fill in any holes in the regions, since they are most likely red also.
yellowObjectsMask = uint8(imfill(yellowObjectsMask, 'holes&#039

);
subplot(3, 3, 3);
imshow(yellowObjectsMask, []);
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.&#039

;
reply = questdlg(message, 'Continue with Demo?', 'OK','Cancel', 'OK&#039

;
if strcmpi(reply, 'Cancel&#039

% User canceled so exit.
return;
end

% You can only multiply integers if they are of the same type.
% (yellowObjectsMask is a logical array.)
% We need to convert the type of yellowObjectsMask to the same data type as hImage.
yellowObjectsMask = cast(yellowObjectsMask, class(rgbImage));

% Use the yellow object mask to mask out the yellow-only portions of the rgb image.
maskedImageR = yellowObjectsMask .* rgbImage(:,:,1);
maskedImageG = yellowObjectsMask .* rgbImage(:,:,2);
maskedImageB = yellowObjectsMask .* 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 Only the Yellow Objects&#039

;
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(yellowObjectsMask, hImage, sImage, vImage);
if numberOfBlobs > 0
fprintf(1, '\n----------------------------------------------\n&#039

;
fprintf(1, 'Blob #, Area in Pixels, Mean H, Mean S, Mean V\n&#039

;
fprintf(1, '----------------------------------------------\n&#039

;
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 yellow blobs were found.
message = sprintf('No yellow blobs were found in the image:\n%s', fullImageFileName);
fprintf(1, '\n%s\n', message);
uiwait(msgbox(message));
end

subplot(3, 3, 9);
ShowCredits();
message = sprintf('Done!\n\nThe demo has finished.\n\nLook the MATLAB command window for\nthe area and color measurements of the %d regions.', numberOfBlobs);
msgbox(message);

catch ME
errorMessage = sprintf('Error running this m-file:\n%s\n\nThe error message is:\n%s', ...
mfilename('fullpath&#039

, ME.message);
errordlg(errorMessage);
end
return; % from SimpleColorDetection()
% ---------- End of main function ---------------------------------

%----------------------------------------------------------------------------
function [meanHSV, areas, numberOfBlobs] = MeasureBlobs(maskImage, hImage, sImage, vImage)
[labeledImage numberOfBlobs] = bwlabel(maskImage, 8); % Label each blob so we can make measurements of it
if numberOfBlobs == 0
% Didn't detect any yellow blobs in this image.
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&#039

;
blobMeasurementsSat = regionprops(labeledImage, sImage, 'area', 'MeanIntensity&#039

;
blobMeasurementsValue = regionprops(labeledImage, vImage, 'area', 'MeanIntensity&#039

;

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]';

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&#039

;
children = get(hStemLines, 'children&#039

;
set(children(2),'visible', 'off&#039

;
% 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&#039

;
text(double(highThresh + 5), double(0.85 * maxYValue(2)), annotationTextH, 'FontSize', fontSizeThresh, 'Color', [0 .5 0], 'FontWeight', 'Bold&#039

;

% 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&#039

;
text(0.5,1.15, caption, 'Color','r', 'FontSize', 18, 'FontWeight','b', 'HorizontalAlignment', 'Center&#039

;
positionOfLowerRightPlot = get(logoFig, 'position&#039

;
L = 40*membrane(1,25);
logoax = axes('CameraPosition', [-193.4013 -265.1546 220.4819],...
'CameraTarget',[26 26 10], ...
'CameraUpVector',[0 0 1], ...
'CameraViewAngle',9.5, ...
'DataAspectRatio', [1 1 .9],...
'Position', positionOfLowerRightPlot, ...
'Visible','off', ...
'XLim',[1 51], ...
'YLim',[1 51], ...
'ZLim',[-13 40], ...
'parent',gcf);
s = surface(L, ...
'EdgeColor','none', ...
'FaceColor',[0.9 0.2 0.2], ...
'FaceLighting','phong', ...
'AmbientStrength',0.3, ...
'DiffuseStrength',0.6, ...
'Clipping','off',...
'BackFaceLighting','lit', ...
'SpecularStrength',1.1, ...
'SpecularColorReflectance',1, ...
'SpecularExponent',7, ...
'Tag','TheMathWorksLogo', ...
'parent',logoax);
l1 = light('Position',[40 100 20], ...
'Style','local', ...
'Color',[0 0.8 0.8], ...
'parent',logoax);
l2 = light('Position',[.5 -1 .4], ...
'Color',[0.8 0.8 0], ...
'parent',logoax);

return; % from ShowCredits()

**amir653** · 2015-07-21T02:53:49

پاسخ : detect color wavelet image

سلام
کدی که گذاشتین از استانه گذاری روی محیط اچ و اس و وی استفاده می کنه
ولی نتونست رنگ زرد که مثال خودش بود رو حتی به خوبی بدست بیاره!!!!
سوالتون چیه؟؟

اطلاعیه

detect color wavelet image

detect color wavelet image

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