A Novel Neutrosophic Image Segmentation Based on Improved Particle Swarm Optimization Fuzzy C-Means Algorithm

A new neutrosophic image segmentation algorithm based on improved particle swarm optimization fuzzy c-means(IPSO-FCM) is proposed to improve the time-consuming problem of neutrosophic image segmentation. In the novel method, the velocity updating method of PSO algorithm is divided into two kinds, and the objective function obtained by comparing the two velocities is compared. The corresponding velocity of minimum objective function is used as the current generation velocity and the position of the PSO particles is updated. Then the IPSO-FCM applied to the neutrosophic image. The experimental results show that the proposed algorithm can eliminate image noise more effectively than PSO-FCM algorithm, and the relative running time is shorter than that of PSO-FCM algorithm.