License plate recognition based on extension theory

As far as the general license plate number recognition system is concerned, the traditional image recognition function is so often subjected to external factors that the license plate number recognition accuracy is greatly reduced. The factors such as light, weather, and dirty spots on the plate will produce the so-called miscellaneous points and the existence of these miscellaneous points will obviously reduce the accuracy rate of the general license plate number recognition. In this paper, we make use of extension theory to successfully develop an intelligent license plate number recognition system and prove that it can efficiently enhance the recognition accuracy rate by means of the strong antinoise ability of extension theory.