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

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sumaiya khan
sumaiya khan 2019-2-14
回答： Alok Nimrani 2019-2-21
The steps performed for k-means clustering are as follows:
  1. Choose k initial centroids
  2. Compute the distance from each pixel to the centroid
  3. Recalculate the centroids after all the pixels have been assigned
  4. 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.

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Alok Nimrani
Alok Nimrani 2019-2-21
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.

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