基于改进BP神经网络的车牌字符识别  

Vehicle License Plate Recognition Based on Improved BP Network

作　　者：王智文[1] 

机构地区：[1]广西工学院计算机工程系,广西柳州545006

出　　处：《微电子学与计算机》2011年第9期66-69,共4页Microelectronics & Computer

基　　金：国家自然科学基金项目(60873179);广西自然科学基金项目(2011GXNSFA018162);深圳市科技计划基础研究项目(JC200903180630A);高等学校博士学科点专项科研基金(20090121110032)

摘　　要：在分析了BP网络学习算法的缺陷的基础上引入动量项和遗传算法对BP网络学习算法进行改进,大大提高了BP网络的收敛速度.对车牌字符图像进行分割并利用sobel算子进行边缘检测来提取字符特征.然后利用改进的BP网络来自动识别车牌字符,提高了识别的速度和正确率.In this article,BP network learning algorithm is improved by using momentum and genetic algorithm after analyzing the defects of the BP network learning algorithm.So the convergence rate of BP network is speeded up greatly.The vehicle license plate character image is segmented and feature is extracted by edge detection using sobel operator.And then license plates of cars are automatically recognized by using improved BP neural network.This algorithm can improve the speed and accuracy for the automatic identification of the license plates of vehicle.

关 键 词：BP网络 动量项 遗传算法 车牌字符定位 车牌字符分割 车牌字符识别 

分 类 号：TP391.3[自动化与计算机技术—计算机应用技术]