MATLAB: Finding centroid of an image with a summed pixel area greater than 120 pixels squared

centroidImage Processing Toolboximage segmentationimregionalmaxregionprops

Hi,

I am trying to find the position of an object in an image. I need to first find connected pixels with intensity values above threshold, which I used imregionalmax function. I know need to identify centroid's with areas greater than 120 pixels squared. I am having no problem using imregionalmax and then regionprops function to find centroid, but am having issues figuring out how to find centroids of objects with pixel areas greater than 120 pixels squared.

Any suggestions?

Best Answer

Heath, no, don't use imregionalmax. Use thresholding followed by bwareaopen followed by bwlabel followed by regionprops:

binaryImage = grayImage > 120;
binaryImage = bwareaopen(binaryImage, 120); % Keep blobs 120 pixels and bigger.
labeledImage = bwlabel(binaryImage);
props = regionprops(labeledImage, 'Centroid');
allCentroids = [props.Centroid];
xCentroids = allCentroids(1:2:end);
yCentroids = allCentroids(2:2:end);

See my thresholding application (to visually/interactively threshold the image) and Image Segmentation Tutorial in my File Exchange: http://www.mathworks.com/matlabcentral/fileexchange/?term=authorid%3A31862

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grayImage = imread('coins.png');
subplot(2,2,1);
imshow(grayImage);
binaryImage = grayImage > 100;
binaryImage = imfill(binaryImage, 'holes'); % Fill holes.
[labeledImage, numObjects] = bwlabel(binaryImage);
stats = regionprops(labeledImage,'Area');
allAreas = [stats.Area]
[~, indexOfLargest] = max(allAreas);
largestBlob = ismember(labeledImage, indexOfLargest)>0;
subplot(2,2,2);
imshow(largestBlob);
title('Largest');
keeperIndexes = 1:numObjects;
keeperIndexes(indexOfLargest) = [];
binaryImage2 = ismember(labeledImage, keeperIndexes)>0;
subplot(2,2,3);
imshow(binaryImage2);
title('All Except Largest');

MATLAB: Regionprops didn’t work

Try this

grayImage = imread('nameimg.png');
% 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, 2, 1);
imshow(grayImage, []);
title('Original Grayscale Image', 'FontSize', fontSize, 'Interpreter', 'None');
binaryImage = im2bw(grayImage);
[labeledImage, numBlobs] = bwlabel(grayImage);
props = regionprops(labeledImage,'Centroid')
allCentroids = [props.Centroid];
xCentroids = allCentroids(1:2:end);
yCentroids = allCentroids(2:2:end);

See my tutorial for a full demo: http://www.mathworks.com/matlabcentral/fileexchange/?term=authorid%3A31862

Best Answer

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