See my demo for extracting the N biggest or smallest blobs. Copy and save to "ExtractBiggestBlob.m" and run it. The main function you want, ExtractNLargestBlobs(), is at the end.
function ExtractBiggestBlob()
clc; % Clear the command window.
close all; % Close all figures (except those of imtool.)
imtool close all; % Close all imtool figures if you have the Image Processing Toolbox.
clear; % Erase all existing variables. Or clearvars if you want.
workspace; % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 20;
% Read in a standard MATLAB gray scale demo image.
folder = fullfile(matlabroot, '\toolbox\images\imdemos');
baseFileName = 'coins.png';
% Get the full filename, with path prepended.
fullFileName = fullfile(folder, baseFileName);
% Check if file exists.
if ~exist(fullFileName, 'file')
% File doesn't exist -- didn't find it there. Check the search path for it.
fullFileName = baseFileName; % No path this time.
if ~exist(fullFileName, 'file')
% Still didn't find it. Alert user.
errorMessage = sprintf('Error: %s does not exist in the search path folders.', fullFileName);
uiwait(warndlg(errorMessage));
return;
end
end
grayImage = imread(fullFileName);
% Get the dimensions of the image.
% numberOfColorBands should be = 1.
[rows, columns, numberOfColorBands] = size(grayImage);
% Display the original gray scale image.
subplot(2, 2, 1);
imshow(grayImage, []);
title('Original Grayscale Image', 'FontSize', fontSize);
% Enlarge figure to full screen.
set(gcf, 'units','normalized','outerposition',[0 0 1 1]);
% Give a name to the title bar.
set(gcf,'name','Demo by ImageAnalyst','numbertitle','off')
% Let's compute and display the histogram.
[pixelCount, grayLevels] = imhist(grayImage);
subplot(2, 2, 2);
bar(pixelCount);
grid on;
title('Histogram of original image', 'FontSize', fontSize);
xlim([0 grayLevels(end)]); % Scale x axis manually.
% Threshold the image to binarize it.
binaryImage = grayImage > 100;
% Fill holes
binaryImage = imfill(binaryImage, 'holes');
% Display the image.
subplot(2, 2, 3);
imshow(binaryImage, []);
title('Binary Image', 'FontSize', fontSize);
% Get all the blob properties. Can only pass in originalImage in version R2008a and later.
[labeledImage, numberOfBlobs] = bwlabel(binaryImage);
blobMeasurements = regionprops(labeledImage, 'area', 'Centroid');
% Get all the areas
allAreas = [blobMeasurements.Area] % No semicolon so it will print to the command window.
menuOptions{1} = '0'; % Add option to extract no blobs.
% Display areas on image
for k = 1 : numberOfBlobs % Loop through all blobs.
thisCentroid = [blobMeasurements(k).Centroid(1), blobMeasurements(k).Centroid(2)];
message = sprintf('Area = %d', allAreas(k));
text(thisCentroid(1), thisCentroid(2), message, 'Color', 'r');
menuOptions{k+1} = sprintf('%d', k);
end
% Ask user how many blobs to extract.
numberToExtract = menu('How many do you want to extract', menuOptions) - 1;
% Ask user if they want the smallest or largest blobs.
promptMessage = sprintf('Do you want the %d largest, or %d smallest, blobs?',...
numberToExtract, numberToExtract);
titleBarCaption = 'Largest or Smallest?';
sizeOption = questdlg(promptMessage, titleBarCaption, 'Largest', 'Smallest', 'Cancel', 'Largest');
if strcmpi(sizeOption, 'Cancel')
return;
elseif strcmpi(sizeOption, 'Smallest')
% If they want the smallest, make the number negative.
numberToExtract = -numberToExtract;
end
%---------------------------------------------------------------------------
% Extract the largest area using our custom function ExtractNLargestBlobs().
% This is the meat of the demo!
biggestBlob = ExtractNLargestBlobs(binaryImage, numberToExtract);
%---------------------------------------------------------------------------
% Display the image.
subplot(2, 2, 4);
imshow(biggestBlob, []);
% Make the number positive again. We don't need it negative for smallest extraction anymore.
numberToExtract = abs(numberToExtract);
if numberToExtract == 1
caption = sprintf('Extracted %s Blob', sizeOption);
elseif numberToExtract > 1
caption = sprintf('Extracted %d %s Blobs', numberToExtract, sizeOption);
else % It's zero
caption = sprintf('Extracted 0 Blobs.');
end
title(caption, 'FontSize', fontSize);
msgbox('Done with demo!');
% Function to return the specified number of largest or smallest blobs in a binary image.
% If numberToExtract > 0 it returns the numberToExtract largest blobs.
% If numberToExtract < 0 it returns the numberToExtract smallest blobs.
% Example: return a binary image with only the largest blob:
% binaryImage = ExtractNLargestBlobs(binaryImage, 1)
% Example: return a binary image with the 3 smallest blobs:
% binaryImage = ExtractNLargestBlobs(binaryImage, -3)
function binaryImage = ExtractNLargestBlobs(binaryImage, numberToExtract)
try
% Get all the blob properties. Can only pass in originalImage in version R2008a and later.
[labeledImage, numberOfBlobs] = bwlabel(binaryImage);
blobMeasurements = regionprops(labeledImage, 'area');
% Get all the areas
allAreas = [blobMeasurements.Area];
if numberToExtract > 0
% For positive numbers, sort in order of largest to smallest.
% Sort them.
[sortedAreas, sortIndexes] = sort(allAreas, 'descend');
elseif numberToExtract < 0
% For negative numbers, sort in order of smallest to largest.
% Sort them.
[sortedAreas, sortIndexes] = sort(allAreas, 'ascend');
% Need to negate numberToExtract so we can use it in sortIndexes later.
numberToExtract = -numberToExtract;
else
% numberToExtract = 0. Shouldn't happen. Return no blobs.
binaryImage = false(size(binaryImage));
return;
end
% Extract the "numberToExtract" largest blob(a)s using ismember().
biggestBlob = ismember(labeledImage, sortIndexes(1:numberToExtract));
% Convert from integer labeled image into binary (logical) image.
binaryImage = biggestBlob > 0;
catch ME
errorMessage = sprintf('Error in function ExtractNLargestBlobs().\n\nError Message:\n%s', ME.message);
fprintf(1, '%s\n', errorMessage);
uiwait(warndlg(errorMessage));
end
