License plate recognition based on rough set

Abstract

License plate recognition belongs to the field of computer vision and pattern recognition, and plays an important role in the field of intelligent transportation. The license plate location is a key technology in license plate recognition; the accuracy in the positioning of a license directly affects the accuracy of character segmentation and character recognition, and has a direct impact on the efficiency of the license plate recognition system. In this chapter, a plate positioning system is constructed based on the knowledge acquisition and knowledge reduction ability of a rough set, as well as the learning ability and generalization ability of a neural network,. By combining the rough set with neural networks and fuzzy logic, a rough fuzzy neural network recognition is proposed. The experimental results show that this system not only simplifies the structure of the system but also improves the generalization capability of knowledge, and improves the accuracy of character positioning. © 2013 Springer Science+Business Media New York.