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A robust image segmentation algorithm based on Alternative Fuzzy C-mean clustering algorithm (AFCM) with Markov Random Field (MRF) is presented in this paper. Due to disregard of spatial constraint information, the results using Fuzzy C-Mean (FCM) and AFCM are corrupted by noise. In order to improve the robustness of noise, the spatial constraint information of an image is represented by MRF with the Gibbs function which is based on the AFCM. Comparison to the FCM, AFCM, FCM-MRF model, and the proposed algorithm has been demonstrated by the simulation and real images. Results show that AFCM-MRF model achieves better performance than other methods.