MATLAB: How to select the object with the largest area

image processingImage Processing ToolboxMATLABobjects

hi…i have i used bwconvhull to detect a certain part of the image, as you can see in the image that there are number of objects with certain centroids. what i want to do is to detect the object with the largest area(1st big one from the left) and neglect the others.

which method should i follow?

i will will be very thankful for your help.

following is the code(its very roughly written as i am still working on it. Sorry for any inconvenience in advance)

CH_objects = bwconvhull(c,'objects');
imshow(CH_objects);
title('Objects Convex Hull');
bwarea(CH_objects)
Ilabel =bwlabel(CH_objects,8);
stat = regionprops(Ilabel,'centroid');
imshow(CH_objects); hold on;
for x = 1: numel(stat)
    plot(stat(x).Centroid(1),stat(x).Centroid(2),'ro');
end

Best Answer

I have a demo for exactly that purpose. Please click the blue link (ExtractBiggestBlob.m) below copy the program to MATLAB and run it.

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MATLAB: Separate two type of object in the image

Do you mean like this:

clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
clear;  % Erase all existing variables. Or clearvars if you want.
workspace;  % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 22;
%--------------------------------------------------------------------------------------------------------

%    READ IN IMAGE
folder = pwd;
baseFileName = 'Q4_4.png';
% Get the full filename, with path prepended.
fullFileName = fullfile(folder, baseFileName);
% Check if file exists.
if ~exist(fullFileName, 'file')
	% The file doesn't exist -- didn't find it there in that folder.
	% Check the entire search path (other folders) for the file by stripping off the folder.
	fullFileNameOnSearchPath = baseFileName; % No path this time.
	if ~exist(fullFileNameOnSearchPath, '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.
% numberOfColorChannels should be = 1 for a gray scale image, and 3 for an RGB color image.
[rows, columns, numberOfColorChannels] = size(grayImage)
if numberOfColorChannels > 1
	% It's not really gray scale like we expected - it's color.
	% Use weighted sum of ALL channels to create a gray scale image.
	grayImage = rgb2gray(grayImage);
	% ALTERNATE METHOD: Convert it to gray scale by taking only the green channel,
	% which in a typical snapshot will be the least noisy channel.
	% grayImage = grayImage(:, :, 2); % Take green channel.
end
% Display the image.
subplot(2, 3, 1);
imshow(grayImage);
axis('on', 'image');
title('Original Grayscale Image', 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;
hFig = gcf;
hFig.WindowState = 'maximized'; % May not work in earlier versions of MATLAB.
drawnow;
%--------------------------------------------------------------------------------------------------------
% Binarize the image.
binaryImage = ~imbinarize(grayImage);
% Get rid of particles less than 200 in area.
binaryImage = bwareaopen(binaryImage, 200);
% Eliminate partial blobs - those touching the edge of the image.
binaryImage = imclearborder(binaryImage);
subplot(2, 3, 2);
imshow(binaryImage, []);
axis('on', 'image');
title('Mask Image', 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;
drawnow;
% Find blobs
props = regionprops(binaryImage, 'Centroid', 'Area');
xy = vertcat(props.Centroid)
allAreas = [props.Area];
subplot(2, 3, 3);
histogram(allAreas, 10);
grid on;
title('Histogram of Blob Areas', 'FontSize', fontSize, 'Interpreter', 'None');
xlabel('Area', 'FontSize', fontSize, 'Interpreter', 'None');
ylabel('Count', 'FontSize', fontSize, 'Interpreter', 'None');
% Get blobs smaller than 2500
[labeledImage, numBlobs] = bwlabel(binaryImage);
smallIndexes = find(allAreas < 2500);
largeIndexes = find(allAreas >= 2500);
% Extract the small blobs with ismember()
smallBlobs = ismember(labeledImage, smallIndexes);
subplot(2, 3, 4);
imshow(smallBlobs);
title('Small Blobs', 'FontSize', fontSize, 'Interpreter', 'None');
% Extract the large blobs with ismember()
largeBlobs = ismember(labeledImage, largeIndexes);
subplot(2, 3, 5);
imshow(largeBlobs);
title('Large Blobs', 'FontSize', fontSize, 'Interpreter', 'None');

MATLAB: Number of Object in binary image

Try this:

bw = imread('bw.png');
if ndims(bw) > 1
	bw = bw(:,:,1);
end
% Threshold
bw = bw > 128;
subplot(1, 2, 1);
imshow(bw, []);
% Fill holes
bw = imfill(bw, 'holes');
% Get areas
props = regionprops(bw, 'Area');
sortedAreas = sort([props.Area], 'descend')
% Looks like we need to throw away any blobs less than 1000 pixels or so
bw = bwareaopen(bw, 1000);
subplot(1, 2, 2);
imshow(bw);
% Count the blobs
[labeledImage, numBlobs] = bwlabel(bw);
fprintf('Found %d shapes.\n', numBlobs);

Best Answer

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MATLAB: Number of Object in binary image

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