MATLAB: Image segmentation of connected shapes problem

black and whitedigital image processingimage analysisimage processingImage Processing Toolboximage segmentation

Hello, Below is the code I used to segment the image however when there are are connected shapes (shown in the img) the code take it as one object. I want it to take it as separate object and get the centroid of each. Your help will be very much appreciated. Thank you.
A = imread('image.png');
figure, imshow(A);
title('Original Image');
B = im2bw(A);
B = ~B;
B = 1-B;
B = (B == 0);
figure, imshow(B);
title('Image Without Holes');
C=imfill(B,'holes');
figure,imshow(C);
title('Image With Holes');
label=bwlabel(B);
max(max(label))
im1=(label==1);
for j=1:max(max(label))
    [row, col] = find(label==j);
    len=max(row)-min(row)+2;
    breadth=max(col)-min(col)+2;
    target=uint8(zeros([len breadth]));
    sy=min(col)-1;
    sx=min(row)-1;
for i=1:size(row,1)
    x=row(i,1)-sx;
    y=col(i,1)-sy;
    target(x,y)=A(row(i,1),col(i,1));
end
mytitle=strcat('Object Number:',num2str(j));
figure,imshow(target);title(mytitle);
end
Image
Result: 2 Objects only should be 5 objects

Best Answer

Wrong approach. Simply use imclearborder():
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 = 20;
grayImage = imread('c2.png');
% Get the dimensions of the image.  
% numberOfColorBands should be = 1.
[rows, columns, numberOfColorBands] = size(grayImage)
if numberOfColorBands > 1
  % It's not really gray scale like we expected - it's color.
  % Convert it to gray scale by taking only the green channel.
  grayImage = grayImage(:, :, 2); % Take green channel.
end
% Display the original gray scale image.
subplot(2, 1, 1);
imshow(grayImage, []);
title('Original Grayscale Image', 'FontSize', fontSize, 'Interpreter', 'None');
% Set up figure properties:
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'OuterPosition', [0 0 1 1]);
% Get rid of tool bar and pulldown menus that are along top of figure.
set(gcf, 'Toolbar', 'none', 'Menu', 'none');
% Give a name to the title bar.
set(gcf, 'Name', 'Demo by ImageAnalyst', 'NumberTitle', 'Off') 
% Binarize the image
binaryImage = grayImage > 128;
% Get rid of the background
binaryImage = imclearborder(binaryImage);
% Get rid of small triangle between the circles.
binaryImage = bwareaopen(binaryImage, 1000);
% Display the binary image.
subplot(2, 1, 2);
imshow(binaryImage, []);
title('Binary Image', 'FontSize', fontSize, 'Interpreter', 'None');
% Identify individual blobs by seeing which pixels are connected to each other.
% Each group of connected pixels will be given a label, a number, to identify it and distinguish it from the other blobs.
% Do connected components labeling with either bwlabel() or bwconncomp().
labeledImage = bwlabel(binaryImage, 8);     % Label each blob so we can make measurements of it
% Get all the blob properties.  Can only pass in originalImage in version R2008a and later.
blobMeasurements = regionprops(labeledImage, 'Centroid');
numberOfBlobs = size(blobMeasurements, 1);
hold on;
for k = 1 : length(blobMeasurements)
  x = blobMeasurements(k).Centroid(1);
  y = blobMeasurements(k).Centroid(2);
  plot(x, y, 'r+', 'MarkerSize', 30, 'LineWidth', 3);
  str = sprintf('The centroid of oval %d is at (%.2f, %.2f)', ...
    k, x, y);
  uiwait(helpdlg(str));
end
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