A multilevel thresholding method for image segmentation using a novel hybrid intelligent approach

Swarm intelligence algorithms have been extensively used in clustering based applications e.g. image segmentation which is one of the fundamental components in image analysis and pattern recognition domains. Particle swarm optimization is amongst swarm intelligence algorithms that performs based on population and random search. In this paper, a hybrid algorithm based on PSO, k-means and learning automata is proposed for image segmentation. In the proposed algorithm, learning automata is responsible for activating and deactivating PSO and k-means methods based on current conditions of the segmentation problem. The proposed approach along with other comparative studies has been applied for segmenting benchmark images. Efficiency of the proposed method has been compared with that of other methods and experimental results show the superiority proposed algorithm.