ISSN ONLINE(2278-8875) PRINT (2320-3765)

All submissions of the EM system will be redirected to Online Manuscript Submission System. Authors are requested to submit articles directly to Online Manuscript Submission System of respective journal.

Research Article Open Access

Comparative Study of Different Clustering Algorithms

Abstract

This paper presents a detailed study and comparison of different clustering based image segmentation algorithms. The traditional clustering algorithms are the hard clustering algorithm and the soft clustering algorithm. We have compared the hard k-means algorithm with the soft fuzzy c- means (FCM) algorithm. To overcome the limitations of conventional FCM we have also studied Kernel fuzzy c- means (KFCM) algorithm in detail. The K-means algorithm is sensitive to noise and outliers so, an extension of K-means called as Fuzzy c- means (FCM) are introduced. FCM allows data points to belong to more than one cluster where each data point has a degree of membership of belonging to each cluster. The KFCM uses a mapping function and gives better performance than FCM in case of noise corrupted images.

A.J.Patil, C.S.Patil, R.R.Karhe, M.A.Aher

To read the full article Download Full Article | Visit Full Article