Double weighted FCM algorithm for color image segmentation

In this paper, we propose a double weighted fuzzy clustering method for color image segmentation. In order to improve the performance of image segmentation by FCM algorithm, we use the window-based point density weighted method to calculate the membership matrix, at the same time, the relietF algorithm is used to assign weights to the components of a true color image. Firstly, RGB color image is transformed into a HSI space. Then, by using the traditional FCM clustering algorithm, the initial membership values could be obtained, which are used to further conduct FCM in the next iteration. Finally, experiments show that by comparing with the standard FCM algorithm the proposed method can get good performances on image segmentation.