Design And Implementation Of Automobile License Plate Recognition System Based On Matlab

The Automatic License Plate Recognition System(LPR)uses digital image processing techniques to locate and identify characters on the license plate number and outputs the result as a text string or other type of data format that can be easily understood by the operator.monitoring applications that require automatic control of the presence and identification of motor vehicles through their license plate numbers,such as automatic electronic toll collection ? LPR applications for the modern management of highways and urban transport With great convenience,the development of pattern recognition has been further promoted.In this paper,based on the analysis of the working mechanism of convolutional neural networks,the local weighted convolutional neural network method is introduced into the specific application of intelligent transportation system.This feature can be directly input through the multi-dimensional network input vector image.Can have better results in image recognition and processing,avoiding the complexity in the feature extraction process.This dissertation aims at the subject of vehicle license plate recognition based on convolutional neural network,summarizes the research status and achievements of domestic and foreign scholars,and introduces the principle of image recognition using convolutional neural network.Based on the analysis and study of the classical neural network structure LeNet-5,the improved convolutional neural network ILeNeT-5 is applied to the license plate recognition problem.Based on the MATLAB platform,the development of the application program is completed,and the final completion is based on the volume.Research on Vehicle License Plate Recognition under Product Neural Network.The license plate recognition based on convolutional neural network studied in this paper is based on the advantage of neural network,using an improved ILeNeT-5 neural network to identify the license plate,which optimizes the parameters of convolution and sampling layers in the network.In a special situation,it also improves the recognition rate of license plates,and can effectively improve the recognition degree of license plates.This has great social significance for the construction of intelligent transportation systems.