Color-Based Segmentation Using the L*a*b* Color Space

Hi everyone. I'm trying to count the number of elements in this picture via color-based segmentation. I'm following the tutorial at this link: https://es.mathworks.com/help/images/examples/color-based-segmentation-using-the-l-a-b-color-space.html Anyway, in the demo he takes 'load coordinates' while I want to get 3 roipoly functions to get the thresholds for the three colors and then save them into 'region coordinates' so that the loop at line 14 (and the code) flows. Thanks.

Answer 1

[Akira Agata]

Looking at your image, there are obviously 4 colors --- blue, green, red and dark brown (=background). So I believe Color-Based Segmentation Using K-Means Clustering example page will be help. The following is an example of k-means-based clustering of your image.

% Read the image and convert to L*a*b* color space
I = imread('Crop.jpg');
Ilab = rgb2lab(I);

% Extract a* and b* channels and reshape
ab = double(Ilab(:,:,2:3));
nrows = size(ab,1);
ncols = size(ab,2);
ab = reshape(ab,nrows*ncols,2);

% Segmentation usign k-means
nColors = 4;
[cluster_idx, cluster_center] = kmeans(ab,nColors,...
  'distance',     'sqEuclidean', ...
  'Replicates',   3);

% Show the result
pixel_labels = reshape(cluster_idx,nrows,ncols);
imshow(pixel_labels,[]), title('image labeled by cluster index');

[giacomo]

Thank you! After the segmentation I created a code to interactively select the diameter of the elements' incircle.

 >> h = ginput(2);
    diameter = sqrt((h(2)-h(1))^2+(h(4)-h(3))^2);
    BlobArea = 3.14*(diameter^2)/4;

How can I count the number of blobs? I know there are examples by Image Analyst but I cannot adapt them to my case. I'd also like to use the infos about the incircle so that all blobs with area < BlobArea won't be counted, while blobs with much bigger area than that (see objects sharing borders with eachother) will have their area divided by BlobArea to get a more reasonable value of number of blobs. Thanks