Particle Swarm Image Segmentation Based on K-means

A new algorithm for image segmentation based on k-mean and particle swarm optimization algorithm is proposed in the paper. K-mean clustering algorithm is a local search algorithm because it is easily trapped local optimum and is sensitive to initial value effectively. On the other hand, particle swarm optimization algorithm is a global optimization algorithm. By incorporating the local search ability of k-mean algorithm and the global optimization ability of PSO and taking the criterion function of k-mean as the object function of PSO, a new hybrid color image segmentation algorithm based on particle swarm optimization and k-mean algorithm is proposed. Experiments show that the new algorithm can get the optimal quantizated image by PSNR and RMSE.