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
Full Text (PDF, 1158KB), PP.30-36
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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