MATLAB: How can i choose the k initial centroids far away from each other in k-means clustering based image segmentation

k-meanssegmentaion

The steps performed for k-means clustering are as follows:

Choose k initial centroids
Compute the distance from each pixel to the centroid
Recalculate the centroids after all the pixels have been assigned
Repeat steps 2 and 3 until the same points are assigned to each cluster in consecutive rounds.

How can i choose the k-initial centroids, such that they are far from each other.

Best Answer

You can make use of k-means++ algorithm to choose the initial centroids far away from each other. This algorithm is the one used by default while performing k-means clustering using the k-means function in MATLAB.

Hope this helps.

Related Solutions

MATLAB: Save different values of the same table from a loop

T2 = cell(length(centroid_clust),1)
for k=1:length(centroid_clust)
     
  separate_areas(1,k)=[area_clust(k).Area];
   c=[centroid_clust(k).Centroid];
  text(c(1), c(2), sprintf('%d', k));  
Cluster(k,:)=k;
Area_of_cluster(k,:)=area_clust(k).Area;
Eccentricity_of_cluster(k,:)=eccentricity_clust(k).Eccentricity ;  
Euler_of_cluster(k,:)=euler_clust(k).EulerNumber;
Perimeter_of_cluster(k,:)=perimeter_clust(k).Perimeter;
Orientation_of_cluster(k,:)=orientation_clust(k).Orientation;
T2{k}= table(Cluster,Area_of_cluster,Eccentricity_of_cluster,Euler_of_cluster,Perimeter_of_cluster,Orientation_of_cluster)
end

MATLAB: Image segmentation by k-means algorithm

https://in.mathworks.com/help/stats/kmeans.html

https://in.mathworks.com/help/stats/k-means-clustering.html

Best Answer

Related Solutions

MATLAB: Save different values of the same table from a loop

MATLAB: Image segmentation by k-means algorithm

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