An image clustering segmentation model combined with variational level set and fuzzy clustering is proposed in this paper. An external fuzzy clustering energy based on the local image information and a new regularization energy with respect to the zero level set are introduced in the energy functional, which makes the proposed model robust in noisy image segmentation. An internal energy that forces the level set function to be close to a signed distance function is introduced in the energy functional, which can completely eliminate the need of the expensive periodical re-initialization procedure for level set function during its evolution. Furthermore, this paper proposes a variational formulation to update the cluster centers in the procedure of clustering, which realizes the semi-supervised clustering segmentation. The experimental results show that the proposed model, compared with the FCM clustering model, CV model and Samson model, can reduce the influence of noise and get better segmentation results for different kinds of images.