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A Network of Dynamically Coupled Elements for Pixel Clustering

Self-organization is a highly observed process of brain to solve several cognitive tasks and many artificial systems based on this mechanism have been developed. In this paper, a self-organized dynamical model is proposed for pixel clustering. This approach employs a network consisting of interacting elements with each representing a pixel value and receiving attractions from other elements within a certain neighborhood. Those attractions, determined by a predefined similarity measure, drive the elements to converge to their corresponding cluster center. With this model, neither the number of pixel clusters nor the initial guessing of cluster centers is required. Computer simulations for clustering of real images are performed to show the efficiency of the proposed approach.