现代电子技术2016，Vol.39Issue(16)：102-104,107,4.DOI:10.16652/j.issn.1004-373x.2016.16.027
车牌图像特征提取及改进神经网络的识别算法研究
Research on feature extraction of license plate image and recognition algorithm based on improved neural network
摘要
Abstract
The feature extraction and recognition algorithm of license plate character image are studied. The BP neural net⁃work recognition algorithm is used to identify the license plate character image. Since the conventional BP neural network algo⁃rithm is easy to fall into local minimum value and low convergence efficiency,and difficult to determine the network structure parameters in training process,moreover,since the selection of BP network structure parameters has great influence on the per⁃formance of the algorithm,and the parameters selection is usually based on the empirical formula and has prodigious random⁃ness and blindness,the performance of the algorithm can’t be guaranteed. Therefore,the PSO algorithm is used to optimize the performance of BP neural network algorithm,which has fast convergence rate and is suitable for global search. The improved BP neural network algorithm for the dual particle swarm optimization is studied. The recognition algorithm is studied with the experi⁃ment of license plate recognition. The results show that the recognition accuracy of Chinese characters recognition model,letters recognition model and mixed recognition model established by means of the improved neural network algorithm is superior to that of the model established with conventional neural network algorithm,and the recognition algorithm has good recognition perfor⁃mance.关键词
车牌字符识别/特征提取/神经网络/粒子群优化算法Key words
license plate character recognition/feature extraction/neural network/particle swarm optimization algorithm分类
信息技术与安全科学引用本文复制引用
李战明,杨红红..车牌图像特征提取及改进神经网络的识别算法研究[J].现代电子技术,2016,39(16):102-104,107,4.基金项目
教育部博士点基金 （）
