Image Segmentation using Enhanced K-means clustering with divide and Conquer Approach

This paper present image segmentation using Enhanced k-means clustering with divide and conquer approach. First we enhanced the k-means clustering and then segment the image using enhanced approach. K-means is one of the most popular clustering algorithms. The final clustering result of the k-means clustering algorithm greatly depends upon the correctness of the initial centroids, which are selected randomly. Many improvements were already proposed to improve the performance of k-means, but most of these require initial k centroids .In this paper we have proposed a new method enhanced k-means clustering algorithm with divided and conquer algorithm to find the initial centroids with reduced time complexity. In this paper we fixed the initial centroids which gives best result and in the final step we segment the image using enhanced clustering algorithm.