华侨大学学报（自然科学版）2017，Vol.38Issue(1)：113-116,4.DOI:10.11830/ISSN.1000-5013.201701022
径向基神经网络算法在车牌字符识别中的应用
Application of Radial Basis Function Neural Network Algorithm in License Plate Character Recognition
摘要
Abstract
A vehicle license plate character recognition algorithm based on radial basis function network is proposed.In the preprocessing stage,image noise is removed and the contrast of image is enhanced by adaptive threshold segmentation and grayscale;at the character segmentation stage,using the limit element method to determine the position of independent character segmentation;in the stage of character recognition,the train-ing of the radial basis function neural network is used to construct the character sub block image library.The character recognition algorithm based on back propagation (BP)neural network and the character recognition algorithm based on support vector machine (SVM)are selected,and the method is compared with the method in this paper.Experimental results show that this method has obvious advantages in recognition accuracy,and it is more suitable for vehicle license plate character recognition.关键词
汽车车牌/字符分割/字符识别/径向基网络Key words
vehicle license plate/character segmentation/character recognition/radial basis function network分类
信息技术与安全科学引用本文复制引用
刘智..径向基神经网络算法在车牌字符识别中的应用[J].华侨大学学报（自然科学版）,2017,38(1):113-116,4.基金项目
广西教育厅高校科研资助项目 （）
