SOME VARIANTS OF K-MEANS CLUSTERING WITH EMPHASIS ON IMAGE SEGMENTATION
In this paper we focus on some variants of K means clustering approach which can be used for image segmentation also. In k-means clustering, we are given a set of n data points in d-dimensional space and an integer k and the problem is to determine a set of k points in , called centers, so as to minimize the mean squared distance from each data point to its nearest center. A popular heuristic for k-means clustering is Lloyd's algorithm. In this paper we have analyzed and presented some extensions that increase its range of applicability.
Sheetal Aggarwal, Ashok
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