To overcome the noise sensitiveness of conventional fuzzy c-means (FCM) clustering
algorithm, a novel extended FCM algorithm for image segmentation is presented in this …

Fuzzy clustering techniques, especially fuzzy c-means (FCM) clustering algorithm, have
been widely used in automated image segmentation. However, as the conventional FCM …

Fuzzy c-means (FCM) algorithm is one of the most popular methods for image segmentation.
However, the standard FCM algorithm must be estimated by expertise users to determine …

The generalized fuzzy c-means clustering algorithm with improved fuzzy partition (GFCM) is
a novel modified version of the fuzzy c-means clustering algorithm (FCM). GFCM under …

Fuzzy c-means (FCM) algorithms with spatial constraints (FCM_S) have been proven
effective for image segmentation. However, they still have the following disadvantages:(1) …

Fuzzy clustering algorithm is widely used in image segmentation. Possibilistic c-means
algorithm overcomes the relative membership problem of fuzzy c-means algorithm, and has …

Much research has been conducted on fuzzy c‐means (FCM) clustering algorithms for
image segmentation that incorporate the local neighbourhood information into their …

In this study, we propose a new robust Fuzzy C-Means (FCM) algorithm for image
segmentation called the patch-based fuzzy local similarity c-means (PFLSCM). First of all …

In this paper, we present an improved fuzzy C-means (FCM) algorithm for image
segmentation by introducing a tradeoff weighted fuzzy factor and a kernel metric. The …

As an effective image segmentation method, the standard fuzzy c-means (FCM) clustering
algorithm is very sensitive to noise in images. Several modified FCM algorithms, using local …