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ImageAnalyst <imageanalyst@mailinator.com> wrote in message <390d8c4a-973f-4454-b20f-ff98b30f1c1c@e7g2000yqf.googlegroups.com>...
> Vivian Harvey:
> This is really easy. Just follow my demo
> http://www.mathworks.com/matlabcentral/fileexchange/25157
> You have to put in an imclearborder() to get rid of the bright
> background after you threshold it, but other than that it will work
> with very little modification. Here is the modified blobsdemo for
> you:
> By the way, your image has an extension of PNG but it is really a BMP
> image.
> Also, be sure to join any lines split apart by the newsreader.
> It may look long but it's basically these parts
> 1. threshold.
> 2. imclearborder
> 3. label
> 4. regionprops
> 5. ismember() to retain only the round blobs and throw away the non-
> round blobs.
>
> %------------------------------------------------------------------------------------------------
> % 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 = 7.5 seconds the first run and 2.5 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
> fullFilename = 'C:\Documents and Settings\userName\My Documents
> \Temporary stuff\Line Drawings.bmp';
> rgbOriginalImage = imread(fullFilename);
> % It's color, so take just the red channel:
> originalImage = rgbOriginalImage(:,:,1);
> 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 <.
> binaryImage = imclearborder(binaryImage, 4);
>
> % 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);
> numberOfBoundaries = size(boundaries);
> for k = 1 : numberOfBoundaries
> 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 (ECD) Solidity\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.
> blobSolidity = blobMeasurements(k).Solidity; % Get solidity.
> 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 %8.1f\n',
> k, meanGL, blobArea, blobPerimeter, blobCentroid, blobECD,
> blobSolidity);
> % 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).
> allBlobSolidities = [blobMeasurements.Solidity];
> % Get a list of the blobs that meet our criteria and we need to keep.
> allowableIndexes = allBlobSolidities > 0.8; % Take the round objects.
> keeperIndexes = find(allowableIndexes);
> % 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);
> subplot(3, 3, 7);
> imshow(keeperBlobsImage, []);
> axis square;
> title('"Keeper" blobs (round blobs)');
> % Re-label with only the keeper blobs kept.
> labeledRoundBlobImage = bwlabel(keeperBlobsImage, 4); % 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, 8);
> imshow(labeledRoundBlobImage, []);
> axis square;
> title('Re-labeled blobs (round blobs)');
>
> 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);
Thank you for the above. I will try to see whether this works and I hope I will be smart enough to incorporate the methodology :) ..Regards
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