A novel method for multi-level image thresholding using particle swarm Optimization algorithms

The selection of threshold is one the general methods in image segmentation, but often the selection of the optimal value for threshold is a challenge for researchers. In this paper we proposed a fast and optimal method for selection of good enough threshold value based on Particle Swarm Optimization algorithms (PSOa). To achieve the fast speed in the proposed method, five types of PSO algorithms have been evaluated. The brief Introduction of the principle OTSU, as the fitness function of PSO algorithm is given. Moreover, the proposed method has been applied in various experiments in comparison with famous methods based on several standard test Images. Experimental results demonstrated that the proposed method outperformed better in comparison of other methods.