Flexible 2- Tree Fuzzy C Means Based Image Segmentation.

Nagaraj Balakrishnan; Mithya Varatharaj; Arunkumar R

Author(s)

Nagaraj Balakrishnan Karpagam College of Engineering, Coimbatore, India

Mithya Varatharaj Karpagam College of Engineering,Coimbatore, India

Arunkumar R Karpagam College of Engineering,Coimbatore, India

Abstract

This paper presents an unsupervised optimized method for image segmentation. Generally, a FCM or FCM based image segmentation process is accomplished under the supervision of clustering algorithms. But these algorithms possess the demerit of depending upon supervised user inputs such as number of clusters, iteration required etc. The proposed method improves the Double Cluster Tree Structure (DCTS), which is an unsupervised preliminary process, by managing its boundary structure process before each iteration of FCM clustering. The combined structure of these two algorithms forms Flexible 2-tree Fuzzy C Means (F2TFCM). Unsupervised analysis as well as segmentation of the whole image dataset is attained with the aid of F2TFCM. Substantial improvement in segmentation performance is exhibited by this algorithm.

Publication Details

Page(s) 735-738

DOI DOI not available

Published Journal: Pakistan Journal of Biotechnology, Volume: 14, Issue: 4, Year: 2017

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