The Study Of Basing On The Image Processing In The License Plate Recognition

The License Plate Recognition(LPR) system is the visual system whose goal is the License Plate, and it is one of the research subjects in which the technology of computer vision and pattern recognition is applied. It not only can widely be applied traffic flux detect, but also be applied to traffic control and lead. It can also be applied to some fields where the vehicle breaks the laws, such as airport, seaport, communities' vehicle manage, no halted vehicle' s fee, and vehicle's safe. So it has widely applied in the future. Basing on the current thing, the thesis will expound the course that searches and deals with image of the License Plate. The following is the main and innovating content of the thesis:(1) At the License Plate image location and pick-up. When we accurately locate the License Plate, firstly, we have applied a new horizontal - vertical method that bases on statistics search the early result, then we again used the Hough transform to detect the result. Finally, we gained the License Plate.(2) During the pretreatment phase. At first, the thesis brings forward a new so-called RemoveScatterNoise, then brings forward a new project compare method, and uses it to revise the License Plate on vertical and extrorse direction. Finally, we use the new horizontal way to revise the License Plate on the horizontal direction. (3)On the course of incising the License Plate character. The thesis, firstly, brings forward coarsely incising the License Plate character. Then cutting the larger room than the License Plate character should lie in.(4)On the course of recognizing the License Plate character. Firstly, the thesis brings forward to using the method of 13-character pick-up to pick up character of the License Plate character. Then we used the result to train the Backpropagation Network. Finally, we used the trained result to recognize the character and decided the result. According to the step that the thesis has taken, and the ways that we have taken brought before we write this. The experiment shows the result is effective.