Parametric Comparison of K-means and Adaptive K-means Clustering Performance on Different Images

Madhusmita Sahu, K. Parvathi, M. Vamsi Krishna


Image segmentation takes a major role to analyzing the area of interest in image processing. Many researchers have used different types of techniques to analyzing the image. One of the widely used techniques is K-means clustering. In this paper we use two algorithms K-means and the advance of K-means is called as adaptive K-means clustering. Both the algorithms are using in different types of image and got a successful result. By comparing the Time period, PSNR and RMSE value from the result of both algorithms we prove that the Adaptive K-means clustering algorithm gives a best result as compard to K-means clustering in image segmentation.    


image segmentation; K-means clustering; adaptive K-means clustering; MRI color and gray color image; satellite image; PSNR & RMSE etc.

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ISSN 2088-8708, e-ISSN 2722-2578