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From: parkpoom on 10 Mar 2010 09:11
this is my pic http://www.uppicweb.com/x/i/iv/img_and.jpg . can anyone help me to find radius in each circle please .Thank a lot T_T
From: Ashish Uthama on 10 Mar 2010 09:14
On Wed, 10 Mar 2010 09:11:05 -0500, parkpoom <khunpark(a)gmail.com> wrote:

> this is my pic http://www.uppicweb.com/x/i/iv/img_and.jpg . can anyone
> help me to find radius in each circle please .Thank a lot T_T

Suggestion:
*Use regionprops
*Choose structures whos area is greater than a certain threshold (you
would have to tune this based on the min size you expect these circles to
be)
*Compute radius approximation from this area. area=pi*r^2 => r =
sqrt(area/pi)
From: ImageAnalyst on 10 Mar 2010 09:21
On Mar 10, 9:11 am, "parkpoom " <khunp...(a)gmail.com> wrote:
> this is my pichttp://www.uppicweb.com/x/i/iv/img_and.jpg. can anyone help me to find radius in each circle please .Thank a lot T_T
---------------------------------------------------------------------------------------------

parkpoom / T_T :
What you need to do is to compute the ECD - Equivalent Circular
Diameter (a common measurement although it is not in regionprops).
ECD = sqrt(4 * Area / pi)
divide by 2 to get the equivalent radius.
Go here for a demo on how to get the area.
http://www.mathworks.com/matlabcentral/fileexchange/25157
The demo looks at the area of coins (using the standard MATLAB demo
image) - pretty similar to your situation.

Good luck,
ImageAnalyst
From: parkpoom on 10 Mar 2010 09:27
I can not do Please suggest me some code please
From: ImageAnalyst on 10 Mar 2010 09:56
On Mar 10, 9:27 am, "parkpoom " <khunp...(a)gmail.com> wrote:
> I can not do Please suggest me some code please

----------------------------------------------------------------------------------------------------
Allright, here's the latest version of BlobMeasurement - I haven't
even uploaded this one yet.
This version puts numeric labels on the image and calculates ECD.
Of course, after you understand the demo you'll need to replace the
coins image with your own image.
And, VERY IMPORTANT: Be sure to fix any lines that will get split into
two by the newsreader. Otherwise you'll have lots of syntax errors.
You'll need to join them together into one long line.

%------------------------------------------------------------------------------------------------
% Demo to illustrate simple blob detection, measurement, and
filtering.
% Requires the Image Processing Toolbox (IPT) because it demonstates
some functions
% supplied by that toolbox, plus it uses the "coins" demo image
supplied with that toolbox.
% If you have the IPT (you can check by typing ver on the command
line), you should be able to
% run this demo code simply by copying and pasting this code into a
new editor window,
% and then clicking the green "run" triangle on the toolbar.
% Running time = 7.0 seconds the first run and 1.7 seconds on
subsequent runs.
% A similar Mathworks demo:
% http://www.mathworks.com/products/image/demos.html?file=/products/demos/shipping/images/ipexprops.html
% Code written and posted by ImageAnalyst, July 2009.
%------------------------------------------------------------------------------------------------
% function BlobsDemo()
% echo on;
% Startup code.
tic; % Start timer.
clc; % Clear command window.
clear all; % Get rid of variables from prior run of this m-file.
disp('Running BlobsDemo.m...'); % Message sent to command window.
workspace; % Show panel with all the variables.

% 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

% Read in standard MATLAB demo image
originalImage = imread('coins.png');
subplot(3, 3, 1);
imshow(originalImage);
% Maximize the figure window.
set(gcf, 'Position', get(0, 'ScreenSize'));
% Force it to display RIGHT NOW (otherwise it might not display until
it's all done, unless you've stopped at a breakpoint.)
drawnow;
caption = sprintf('Original "coins" image showing\n6 nickels (the
larger coins) and 4 dimes (the smaller coins).');
title(caption);
axis square; % Make sure image is not artificially stretched because
of screen's aspect ratio.

% Just for fun, let's get its histogram.
[pixelCount grayLevels] = imhist(originalImage);
subplot(3, 3, 2);
bar(pixelCount); title('Histogram of original image');
xlim([0 grayLevels(end)]); % Scale x axis manually.

% Threshold the image to get a binary image (only 0's and 1's) of
class "logical."
% Method #1: using im2bw()
% normalizedThresholdValue = 0.4; % In range 0 to 1.
% thresholdValue = normalizedThresholdValue *
max(max(originalImage)); % Gray Levels.
% binaryImage = im2bw(originalImage,
normalizedThresholdValue); % One way to threshold to binary
% Method #2: using a logical operation.
thresholdValue = 100;
binaryImage = originalImage > thresholdValue; % Bright objects will
be the chosen if you use >.
% binaryImage = originalImage < thresholdValue; % Dark objects will
be the chosen if you use <.

% Do a "hole fill" to get rid of any background pixels inside the
blobs.
binaryImage = imfill(binaryImage, 'holes');

% Show the threshold as a vertical red bar on the histogram.
hold on;
maxYValue = ylim;
hStemLines = stem(thresholdValue, maxYValue(2), 'r');
children = get(hStemLines, 'children');
set(children(2),'visible', 'off');
% Place a text label on the bar chart showing the threshold.
annotationText = sprintf('Thresholded at %d gray levels',
thresholdValue);
% For text(), the x and y need to be of the data class "double" so
let's cast both to double.
text(double(thresholdValue + 5), double(0.5 * maxYValue(2)),
annotationText, 'FontSize', 10, 'Color', [0 .5 0]);
text(double(thresholdValue - 70), double(0.94 * maxYValue(2)),
'Background', 'FontSize', 10, 'Color', [0 0 .5]);
text(double(thresholdValue + 50), double(0.94 * maxYValue(2)),
'Foreground', 'FontSize', 10, 'Color', [0 0 .5]);


% Display the binary image.
subplot(3, 3, 3); imagesc(binaryImage); colormap(gray(256));
title('Binary Image, obtained by thresholding'); axis square;

labeledImage = bwlabel(binaryImage, 8); % Label each blob so we
can make measurements of it
coloredLabels = label2rgb (labeledImage, 'hsv', 'k', 'shuffle'); %
pseudo random color labels

subplot(3, 3, 4);
imshow(labeledImage);
title('Labeled Image, from bwlabel()');
axis square;
subplot(3, 3, 5);
imagesc(coloredLabels);
axis square;
caption = sprintf('Pseudo colored labels, from label2rgb().\nBlobs are
numbered from top to bottom, then from left to right.');
title(caption);

% Get all the blob properties. Can only pass in originalImage in
version R2008a and later.
blobMeasurements = regionprops(labeledImage, originalImage, 'all');
numberOfBlobs = size(blobMeasurements, 1);

% bwboundaries() returns a cell array, where each cell contains the
row/column coordinates for an object in the image.
% Plot the borders of all the coins on the original grayscale image
using the coordinates returned by bwboundaries.
subplot(3, 3, 6); imagesc(originalImage);
title('Outlines, from bwboundaries()'); axis square;
hold on;
boundaries = bwboundaries(binaryImage);
for k = 1 : numberOfBlobs
thisBoundary = boundaries{k};
plot(thisBoundary(:,2), thisBoundary(:,1), 'g', 'LineWidth', 2);
end
hold off;

fontSize = 14; % Used to control size of "blob number" labels put atop
the image.
labelShiftX = -7; % Used to align the labels in the centers of the
coins.
% Print header line in the command window.
fprintf(1,'Blob # Mean Intensity Area Perimeter
Centroid Diameter\n');
% Loop over all blobs printing their measurements to the command
window.
for k = 1 : numberOfBlobs % Loop through all blobs.
% Find the mean of each blob. (R2008a has a better way where you can
pass the original image
% directly into regionprops. The way below works for all versions
including earlier versions.)
thisBlobsPixels = blobMeasurements(k).PixelIdxList; % Get list of
pixels in current blob.
meanGL = mean(originalImage(thisBlobsPixels)); % Find mean
intensity (in original image!)
meanGL2008a = blobMeasurements(k).MeanIntensity; % Mean again, but
only for version >= R2008a

blobArea = blobMeasurements(k).Area; % Get area.
blobPerimeter = blobMeasurements(k).Perimeter; % Get perimeter.
blobCentroid = blobMeasurements(k).Centroid; % Get centroid.
blobECD = sqrt(4 * blobArea / pi); % Compute ECD - Equivalent
Circular Diameter.
fprintf(1,'#%2d %17.1f %11.1f %8.1f %8.1f %8.1f % 8.1f\n', k,
meanGL, blobArea, blobPerimeter, blobCentroid, blobECD);
% Put the "blob number" labels on the "boundaries" grayscale image.
text(blobCentroid(1) + labelShiftX, blobCentroid(2), num2str(k),
'FontSize', fontSize, 'FontWeight', 'Bold');
end

% Put the labels on the rgb labeled image also.
subplot(3, 3, 5);
for k = 1 : numberOfBlobs % Loop through all blobs.
blobCentroid = blobMeasurements(k).Centroid; % Get centroid.
text(blobCentroid(1) + labelShiftX, blobCentroid(2), num2str(k),
'FontSize', fontSize, 'FontWeight', 'Bold');
end

% Now I'll demonstrate how to select certain blobs based using the
ismember function.
% Let's say that we wanted to find only those blobs
% with an intensity between 150 and 220 and an area less than 2000
pixels.
% This would give us the three brightest dimes (the smaller coin
type).
allBlobIntensities = [blobMeasurements.MeanIntensity];
allBlobAreas = [blobMeasurements.Area];
% Get a list of the blobs that meet our criteria and we need to keep.
allowableIntensityIndexes = (allBlobIntensities > 150) &
(allBlobIntensities < 220);
allowableAreaIndexes = allBlobAreas < 2000; % Take the small objects.
keeperIndexes = find(allowableIntensityIndexes &
allowableAreaIndexes);
% Extract only those blobs that meet our criteria, and
% eliminate those blobs that don't meet our criteria.
% Note how we use ismember() to do this.
keeperBlobsImage = ismember(labeledImage, keeperIndexes);
% Re-label with only the keeper blobs kept.
labeledDimeImage = bwlabel(keeperBlobsImage, 8); % Label each blob
so we can make measurements of it
% Now we're done. We have a labeled image of blobs that meet our
specified criteria.
subplot(3, 3, 7);
imshow(labeledDimeImage, []);
axis square;
title('"Keeper" blobs (3 brightest dimes in a re-labeled image)');

% Now use the keeper blob as a mask on the original image.
% This will let us display the original image in the regions of the
keeper blobs.
maskedImageDime = originalImage; % Simply a copy at first.
maskedImageDime(~keeperBlobsImage) = 0; % Set all non-keeper pixels
to zero.
subplot(3, 3, 8);
imshow(maskedImageDime);
axis square;
title('Only the 3 brightest dimes from the original image');

% Now let's get the nickels (the larger coin type)
keeperIndexes = find(allBlobAreas > 2000); % Take the larger objects.
% Note how we use ismember to select the blobs that meet our criteria.
nickelBinaryImage = ismember(labeledImage, keeperIndexes);
maskedImageNickel = originalImage; % Simply a copy at first.
maskedImageNickel(~nickelBinaryImage) = 0; % Set all non-nickel
pixels to zero.
subplot(3, 3, 9);
imshow(maskedImageNickel, []);
axis square;
title('Only the nickels from the original image');

elapsedTime = toc;
% Alert user that the demo is done and give them the option to save an
image.
message = sprintf('Finished running BlobsDemo.m.\n\nElapsed time = %.
2f seconds.', elapsedTime);
message = sprintf('%s\n\nCheck out the figure window for the images.
\nCheck out the command window for the numerical results.', message);
message = sprintf('%s\n\nDo you want to save the pseudo-colored
image?', message);
reply = questdlg(message, 'Done. Save image?', 'Yes', 'No', 'No');
% Note: reply will = '' for Upper right X, 'Yes' for Yes, and 'No' for
No.
if strcmpi(reply, 'Yes')
% Ask user for a filename.
FilterSpec = {'*.tif', 'TIFF images (*.tif)'; '*.*', 'All Files
(*.*)'};
DialogTitle = 'Save image file name';
% Get the default filename. Make sure it's in the folder where this
m-file lives.
% (If they run this file but the cd is another folder then pwd will
show that folder, not this one.
thisFile = mfilename('fullpath');
[thisFolder, baseFileName, ext, version] = fileparts(thisFile);
DefaultName = sprintf('%s/%s.tif', thisFolder, baseFileName);
[fileName, specifiedFolder] = uiputfile(FilterSpec, DialogTitle,
DefaultName);
% Parse what they actually specified.
[folder, baseFileName, ext, version] = fileparts(fileName);
% Create the full filename, making sure it has a tif filename.
fullImageFileName = fullfile(specifiedFolder, [baseFileName '.tif']);
% Save the labeled image as a tif image.
imwrite(uint8(coloredLabels), fullImageFileName);
% Just for fun, read image back into the imtool utility to
demonstrate that tool.
tifimage = imread(fullImageFileName);
imtool(tifimage, []);
end

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