Research on image segmentation based on global optimization search algorithm

In the cluster-based image segmentation algorithm, the initialization was needed in FCM(fuzzy C-means) algorithm and there were lots of local minimum in the objective function, if the initialization obtained the local minimum vicinity point, it would cause a convergence to local minimum. In order to solve this problem, a global optimization search (GOS) algorithm was introduced to the FCM algorithm because it has the global optimization search capabilities. The improved FCM (GOS) has more effective than the traditional method of FCM clustering algorithm through the simulation experiments and theoretical analysis of algorithm performance.