In this paper, we propose an image coding approach based on Alternative Fuzzy c-Means. Our main objective is to provide immediate access to targeted features of interest in a high-quality decoded image. This technique is useful for intelligent devices, as well as for multimedia content-based description standards. Using AFcM reduces the coding time compared to the traditional clustering algorithm FcM. A second coding stage is applied using entropy coding to remove the whole image entropy redundancy. In the decoding phase, we suggest the application of nonlinear anisotropic diffusion, based on the Perona-Malik equation, to enhance the quality of the coded image. Qualitative evaluation confirms the validity of the proposed approach.