A Munkres Particle Swarm optimization algorithm for point pattern matching
Particle Swarm Optimization combines with Munkres algorithm is proposed for Point Pattern Matching in three dimensions. Point Pattern Matching is a fundamental aspect of many fields in computer vision and pattern recognition. The point pattern matching technique could be described as finding an optimal transformation for one point pattern to the other under some measures. The proposed algorithm can be used to perform reliable matching between two different views of an object or scene. A new formula is proposed and used as a reasonable fitness function. The advantages of Munkres and Particle Swarm optimization are used and combined together in this paper. The simulated results show that the new algorithm is very effective.