scholarly journals Fuzzy c-Means Directional Clustering (FCMDC) algorithm using trigonometric approximation

2020 ◽  
Vol 28 (1) ◽  
pp. 140-152
Author(s):  
Orhan KESEMEN ◽  
Özge TEZEL ◽  
Eda ÖZKUL ◽  
Buğra Kaan TİRYAKİ
Keyword(s):  
Trigonometric Approximation ◽  
Fuzzy C Means

Modification of Fuzzy c-Means Method Using a Nonlinear Vector Criterion

2010 ◽  
Vol 42 (12) ◽  
pp. 13-21
Author(s):  
Anatoliy F. Bulat ◽  
Elena M. Kiseleva ◽  
Sergey A. Pichugov ◽  
Oleg B. Blyuss
Keyword(s):  
Vector Criterion ◽  
Fuzzy C Means ◽  
Nonlinear Vector

Multiresolution Bio-Medical Image Segmentation using Fuzzy C-Means Clustering

2019 ◽  
Vol 8 (4) ◽  
pp. 9548-9551
Keyword(s):  
Image Segmentation ◽  
Medical Image Segmentation ◽  
Experimental Result ◽  
Segmentation Method ◽  
Fuzzy C Means ◽  
Fuzzy C Means Clustering ◽  
Robust Image ◽  
Multiple Clusters ◽  
Single Pixel ◽  
Popular Image

Fuzzy c-means clustering is a popular image segmentation technique, in which a single pixel belongs to multiple clusters, with varying degree of membership. The main drawback of this method is it sensitive to noise. This method can be improved by incorporating multiresolution stationary wavelet analysis. In this paper we develop a robust image segmentation method using Fuzzy c-means clustering and wavelet transform. The experimental result shows that the proposed method is more accurate than the Fuzzy c-means clustering.

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