Steve on Image Processing with MATLAB

Image processing concepts, algorithms, and MATLAB


Steve on Image Processing with MATLAB has been archived and will not be updated.

Intensity-weighted centroids

One the measurements provided by regionprops is 'Centroid'. Here's an example of labeling binary objects, computing the centroid of each object, and plotting the centroid location on top of the image.

I = imread('text.png');
L = bwlabel(I);
s = regionprops(L, 'Centroid');
hold on
for k = 1:numel(s)
    plot(s(k).Centroid(1), s(k).Centroid(2), 'r*')
hold off
xlim([0 60])
ylim([0 60])

Last week, reader Daphne asked how to compute the intensity-weighted centroid. That is, if each labeled region corresponds to a region in a gray scale image, how do you compute the centroid weighted by the gray scale pixel values? The easiest way, I think, is to use the both the PixelIdxList and PixelList properties from regionprops. Let's try it with a simple synthetic image (download the image from here):

I = imread('spheres.png');

Now let's threshold and label it:

bw = I < 255;
bw = imfill(bw, 'holes');
L = bwlabel(bw);
imshow(label2rgb(L, @jet, [.7 .7 .7]))

Next, get the PixelIdxList and PixelList for each labeled region:

s = regionprops(L, 'PixelIdxList', 'PixelList');

Each row of the PixelList for a region contains the x and y coordinates of a pixel in that region.

s(1).PixelList(1:4, :)
ans =

    48    94
    48    95
    48    96
    48    97

We can get the grayscale value of pixels in a region by indexing into I with PixelIdxList. By weighting those values with the x and y coordinates, we can compute the centroid.

idx = s(1).PixelIdxList;
sum_region1 = sum(I(idx));
x = s(1).PixelList(:, 1);
y = s(1).PixelList(:, 2);

xbar = sum(x .* double(I(idx))) / sum_region1
xbar =


ybar = sum(y .* double(I(idx))) / sum_region1
ybar =


Let's do that in a loop and superimpose the centroid locations on the image.

hold on
for k = 1:numel(s)
    idx = s(k).PixelIdxList;
    pixel_values = double(I(idx));
    sum_pixel_values = sum(pixel_values);
    x = s(k).PixelList(:, 1);
    y = s(k).PixelList(:, 2);
    xbar = sum(x .* pixel_values) / sum_pixel_values;
    ybar = sum(y .* pixel_values) / sum_pixel_values;

    plot(xbar, ybar, '*')
hold off

Published with MATLAB® 7.5

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