K-means segmentation

This code implements K-means color segmentation

Demo.m shows a K-means segmentation demo

K-means clustering is one of the popular algorithms in clustering and segmentation. K-means segmentation treats each imgae pixel (with rgb values) as a feature point having a location in space. The basic K-means algorithm then arbitrarily locates, that number of cluster centers in multidimensional measurement space. Each point is then assigned to the cluster whose arbitrary mean vector is closest. The procedure continues until there is no significant change in the location of class mean vectors between successive iterations of the algorithms.