K-Means plus plus implementation
You can use a vector quantisation.  You can make a list of each pixel and each adjacent pixel in x+1 and y+1 direction and pick the difference and plot it along a diagonale. Then you can calculate a voronoi diagram and get the mean color and compute a feature vector. It's a bit more effectice then to use a simple grid based mean color.
My score was to get the most frequent color in a image, so I implemented a k-means algorithm.
The algorithm works good, but the result is not the one I was waiting for.
So now I'm trying to do some improvements, the first I thought was to implement k-means++, so I get a beter position for the inicial clusters centers.
First I select a random point, but how can I select the others. I mean how I define the minimal distance between them.
Any help for this? Thanks