Applying New Method for Computing Initial Centers of k-Means Clustering with Color Image Segmentation - H. Hassin Alasadi, Abbas (University of Thi-Qar Journal of Science, 2011)
As a classic clustering method, the traditional k-Means algorithm has been widely used inimage processing and computer vision, pattern recognition and machine learning. It is known thatthe performance of the k-means clustering algorithm depends highly on initial cluster centers.Generally initial cluster centers are selected randomly, so the algorithm could not lead to theunique result. In this paper, we present a method to compute initial centers fork-means clustering. Our method based on an efficient technique for estimating the modes of adistribution. We apply the new method in segmentation phase of color images. The experimentalresults appeared quite satisfactory.