License Plate Recognition System Based On Wavelet Transform And Neural Network Research

In this dissertation, modern signal processing technique, namely wavelet technology is applied to the intelligent transportation field, which is License Plate Recognition System. And improved BP neural network is adopted to recognize license plate characters. The main contents and achievements are as follows:Firstly, the car images are processed by gray transformation and smooth filtering. By way of analyzing the methods of traditional image enhancement, we put forward an algorithm of high-frequency nonlinear enhancement based on the wavelet transformation. Combining with algorithms of edge detection and morphology processing and projection method, we put forward an algorithm of license plate location based on the wavelet transformation.Secondly, the license plate images are processed by binary method and correcting inclination angle. We put forward an algorithm of local adaptive threshold removing noise based on the wavelet transformation. During the process of character segmentation, we remove the margin height of the license plate area, use vertical projection information and the prior knowledge to get single characters, look for the morphology connected domain of the character, cut off the rectangle minimal area, and combine the error segmentations.Finally, we normalize the character images and make them thinner; By way of classified recognition, we use improved BP neural network to recognize license plate characters.