Adaptive segmentation method based on particle swarm optimization algorithms

A new method for image segmentation based on particle swarm optimization (PSO) algorithms is presented. Particle swarm optimization algorithms are a stochastic global optimization technique. The algorithms find optimal regions of complex search spaces through the interaction of individuals in a population of particles. The method based on improved optimal weighted entopic threshold is implemented using PSQ. Optimum parameters suitable for this algorithm based on improved PSO are given. The experimental results indicate that the new approach can shorten the computational time compared with other traditional ways, and is effective for image segmentation.