1 简介
The fuzzy c-means (FCM) algorithm is a popular method for data clustering andimage segmentation. However, the main problem of this algorithm is that it is very sensitive to the initialization ofprimary clusters, so it may not perform well in segmenting complex images. Another problem with theFCM is the equal importance of the image features used during thesegmentation process, which causes unstable performance on different images. In this paper, we propose an FCM-based color image segmentation approach, termed CGFFCM, applying an automatic cluster weighting scheme to reduce the sensitivity to the initialization, and a group-local
