MATLAB: How to extract boundary coordinates of multiple objects in an image

image analysisimage processingimage segmentationMATLAB

Hi, I am working on a path planning project which requires me to find the boundary (in the form of coordinates) of three black regions in the picture given. When I use convhull(after finding the coordinates of the black portion), it gives me the entire region enclosed within the boundary. Is there a way to get the boundary coordinates of the black portion (separately). Thank you! P.S- I don't require the red dot.

Matlab code is appreciated.

Best Answer

Yes. Use bwboundaries().

% Extract red channel and threshold it.
binaryImage = rgbImage(:,:, 1) < 128; 
% Extract the 3 largest blobs ONLY.
binaryImage = bwareafilt(binaryImage, 3);
% Find the boundaries.  Each boundary is in a cell.
boundaries = bwboundaries(binaryImage);
numberOfBoundaries = size(boundaries, 1);
% Display each boundary over the image in red.
hold on;
for k = 1 : numberOfBoundaries
  thisBoundary = boundaries{k}; % Pull N by 2 array from k'th cell.
      % Get x and y from the N-by-2 array.
      x = thisBoundary(:,2);
      y = thisBoundary(:,1);
      plot(x, y, 'r', 'LineWidth', 2); % Plot outline over blob.
end
hold off;

Related Solutions

MATLAB: Crop dark area and display the face only

Convert to grayscale and then threshold and find the bounding box

clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
imtool close all;  % Close all imtool figures.
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 the color image.
folder = pwd;
baseFileName = 'm2.bmp';
% Get the full filename, with path prepended.
fullFileName = fullfile(folder, baseFileName);
if ~exist(fullFileName, 'file')
  % 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.', fullFileName);
    uiwait(warndlg(errorMessage));
    return;
  end
end
rgbImage = imread(fullFileName);
% Get the dimensions of the image.  numberOfColorBands should be = 3.
[rows, columns, numberOfColorBands] = size(rgbImage);
% Display the original color image.
subplot(2, 3, 1);
imshow(rgbImage, []);
axis on;
title('Original Color Image', 'FontSize', fontSize);
drawnow;
% Enlarge figure to full screen.
set(gcf, 'units','normalized','outerposition',[0 0 1 1]);
% Histogram the red channel, but there is a huge spike at 255 so let's not count those.
subplot(2, 3, 2);
grayImage = rgb2gray(rgbImage);
imshow(grayImage, []);
title('Gray Scale version', 'FontSize', fontSize);
subplot(2, 3, 3);
histogram(grayImage(grayImage<255))
grid on;
title('Histogram of Gray Scale Image', 'FontSize', fontSize);
someThresholdValue = 150;
binaryImage = grayImage > someThresholdValue;
% Take largest blob
binaryImage = bwareafilt(binaryImage, 1);
subplot(2, 3, 4);
imshow(binaryImage);
grid on;
title('Binary Image', 'FontSize', fontSize);
% Label the binary image.
labeledImage = bwlabel(binaryImage);
props = regionprops(labeledImage, 'BoundingBox');
bbox = props.BoundingBox
croppedImageRGB = imcrop(rgbImage, bbox);
subplot(2, 3, 5);
imshow(croppedImageRGB);
grid on;
title('Cropped RGB Image', 'FontSize', fontSize);
% Gray scale version of cropped image
croppedImageGray = imcrop(grayImage, bbox);
subplot(2, 3, 6);
imshow(croppedImageGray);
grid on;
title('Cropped Gray Scale Image', 'FontSize', fontSize);

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');

Best Answer

Related Solutions

MATLAB: Crop dark area and display the face only

MATLAB: Separate two type of object in the image

Related Question