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International Journal of Intelligent Systems and Applications(IJISA)

ISSN: 2074-904X (Print), ISSN: 2074-9058 (Online)

Published By: MECS Press

IJISA Vol.4, No.7, Jun. 2012

Image Segmentation Techniques for Noisy Digital Images based upon Fuzzy Logic- A Review and Comparison

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Author(s)

Prabhjot Kaur, Nimmi Chhabra

Index Terms

Fuzzy Clustering;Fuzzy C-Means;Robust Image Segmentation;FCM TYPE-II,;Intuitionistic FCM

Abstract

This paper presents a comparison of the three fuzzy based image segmentation methods namely Fuzzy C-Means (FCM), TYPE-II Fuzzy C-Means (T2FCM), and Intuitionistic Fuzzy C-Means (IFCM) for digital images with varied levels of noise. Apart from qualitative performance, the paper also presents quantitative analysis of these three algorithms using four validity functions-Partition coefficient (V_pc), Partition entropy (V_pe), Fukuyama-Sugeno (V_fs), and Xie-Beni (V_xb) functions and also compared the performance on the basis of their execution time.

Cite This Paper

Prabhjot Kaur, Nimmi Chhabra,"Image Segmentation Techniques for Noisy Digital Images based upon Fuzzy Logic- A Review and Comparison", International Journal of Intelligent Systems and Applications(IJISA), vol.4, no.7, pp.30-36, 2012. DOI: 10.5815/ijisa.2012.07.04

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