Active Contour Model Based on Multi-Population Particle Swarm Optimization

In this paper, the Particle Swarm Optimization (PSO) is utilized to enhance the concavity searching for the control points of Active Contour Model (ACM). In the traditional methods for ACM, the best candidates are searched in a small window. Consequently, the boundary concavities cannot be searched accurately. Some improvements have been made in the past to enlarge the searching space, yet they are still time-consuming. To overcome these drawbacks, a multi-population particle swarm optimization technique is adopted in this paper to reduce the search time but in a larger searching window. This optimizer inherits the spirit of the original PSO as well as shares information among the swarms surrounding control points. Experimental results demonstrate that the proposed method can improve the search of object concavities without spending extra time.