An Improved Fast Fuzzy Clustering Image Segmentation Algorithm

Abstract

Fuzzy C-means (FCM) clustering algorithm for image segmentation is simple, intuitive and easy to implement, However, there are some problems such as large amount of computation, slow computation speed and poor anti-noise ability. For this reason, this paper proposes an improved fast FCM algorithm (FFCM), This method firstly integrates spatial information into standard FCM algorithm, The image is mapped from pixel space to its gray histogram feature space, and fast clustering is realized. Then, on the basis of fast clustering, the neighborhood characteristics of pixels are fully utilized, and the classification of image pixels is divided according to the principle of maximum membership degree, and the membership degree function is improved to some extent. The experimental results show that the method can segment images quickly and effectively, and has good anti-noise capability.