基于混合神经网络的车牌字符识别技术

doi:10.16180/j.cnki.issn1007-7820.2019.09.011

摘要/Abstract

摘要：

车牌识别是智能交通系统的重要组成部分,其关键是车牌字符识别技术。单一的神经网络难以识别模糊的车牌字符,文中提出了一种混合神经网络实现车牌字符识别技术。该混合神经网络结合联想记忆与BP神经网络,对输入的字符进行两次判别,经过训练、特征提取得到检测结果。通过在不同的噪声和不同的角度实验表明,采用混合神经网络具有更高的识别精度。

关键词: BP神经网络, 联想记忆网络, 字符识别, 混合神经网络

Abstract:

License plate recognition was an important part of the intelligent transportation system, and the key was the license plate character recognition technology. A single neural network was difficult to identify fuzzy license plate characters, and a hybrid neural network was proposed to realize license plate character recognition technology. The hybrid neural network combined associative memory with BP neural network to discriminate the input characters twice. After training and feature extraction, the detection results were obtained. Experiments with different noises and different angles showed that the hybrid neural network had higher recognition accuracy.

Key words: BP neural network, associative memory network, character recognition, hybrid neural network

中图分类号:

TP391

张长青,杨楠. 基于混合神经网络的车牌字符识别技术[J]. 电子科技, 2019, 32(9): 51-54.

ZHANG Changqing,YANG Nan. License Plate Character Recognition Technology Based on Hybrid Neural Network[J]. Electronic Science and Technology, 2019, 32(9): 51-54.

图/表 6

图1

图2

图3

图4

图5

图6

参考文献 16

[1]	鲁江坤, 万聿枫, 曹龙汉 . 一种基于图像识别的燃气表远程直读系统研究[J]. 重庆邮电大学学报:自然科学版, 2018,30(5):627-632.
	Lu Jiangkun, Wan Yifeng, Cao Longhan . A remote direct reading system for gas meters based on image recognition[J]. Journal of Chongqing University of Posts and Telecommunications: Natural Science Edition, 2018,30(5):627-632.
[2]	杜媛 . 基于图像分割与多特征模型的车牌识别算法[J]. 国外电子测量技术, 2018,37(8):20-24.
	Du Yuan . License plate recognition algorithm based on image segmentation and multi-feature model[J]. Foreign Electronic Measurement Technology, 2018,37(8):20-24.
[3]	曾泉, 谭北海 . 基于SVM和BP神经网络的车牌识别系统[J]. 电子科技, 2016,29(1):98-101.
	Zeng Quan, Tan Beihai . License plate recognition system based on SVM and BP neural network[J]. Electronic Science and Technology, 2016,29(1):98-101.
[4]	柴伟佳, 王连明 . 一种基于混合神经网络的车牌字符识别方法[J]. 东北师大学报:自然科学版, 2018,50(1):63-67.
	Chai Weijia, Wang Lianming . A license plate character recognition method based on hybrid neural network[J]. Journal of Northeast Normal University:Natural Science Edition, 2018,50(1):63-67.
[5]	张国福, 岳晓峰 . 基于神经网络的字符在线视觉识别研究[J]. 光学技术, 2018,44(1):75-81.
	Zhang Guofu, Yue Xiaofeng . On-line character recognition based on neural network[J]. Optical Technology, 2018,44(1):75-81.
[6]	罗栩豪, 王培, 肖怀成 , 等. 基于改进马尔可夫特征的车牌识别技术[J]. 国外电子测量技术, 2017,36(9):99-103.
	Luo Xunhao, Wang Pei, Xiao Huaicheng , et al. License plate recognition technology based on improved Markov characteristics[J]. Foreign Electronic Measurement Technology, 2017,36(9):99-103.
[7]	孙晶晶, 静大海 . 基于神经网络复杂背景下车牌识别系统的研究[J]. 国外电子测量技术, 2017,36(8):22-25,29.
	Sun Jingjing, Jing Dahai . Research on license plate recognition system based on neural network under complex background[J]. Foreign Electronic Measurement Technology, 2017,36(8):22-25,29.
[8]	周成伟 . 基于卷积神经网络的自然场景中数字识别[J]. 计算机技术与发展, 2017,27(11):101-105.
	Zhou Chengwei . Digital recognition in natural scene based on convolutional neural network[J]. Computer Technology and Development, 2017,27(11):101-105.
[9]	司朋举, 胡伟 . 一种改进的神经网络车牌识别算法研究[J]. 电子测量技术, 2016,39(10):100-103.
	Si Pengju, Hu Wei . An improved neural network license plate recognition algorithms[J]. Electronic Measurement Technology, 2016,39(10):100-103.
[10]	王毅, 王创新, 卢进 , 等. 基于HSV模型和改进AdaBoost算法的车牌检测[J]. 电子科技, 2015,28(2):107-111.
	Wang Yi, Wang Chuangxin, Lu Jin , et al. License plate detection based on HSV model and improved AdaBoost algorithms[J]. Electronic Science and Technology, 2015,28(2):107-111.
[11]	马飞 . 一种基于小波变换和Tophat变换的车牌定位算法[J]. 电子设计工程, 2016,24(22):118-121.
	Ma Fei . A license plate location algorithm based on wavelet transform and Tophat transform[J]. Electronic Design Engineering, 2016,24(22):118-121.
[12]	朱成军, 蒲菊华, 高磊 , 等. 基于Tophat变换和文字纹理的车牌定位算法[J]. 北京航空航天大学学报, 2008,34(5):541-545.
	Zhu Chengjun, Pu Juhua, Gao Lei , et al. License plate location based on tophat transform and texture[J]. Journal of Beijing University of Aeronautics and Astronautics, 2008,34(5):541-545.
[13]	王琳 . 基于模糊聚类汽车牌照分割算法的设计与实现[D]. 济南:山东大学, 2015.
	Wang Lin . Design and implementation of vehicle license plate segmentation algorithms based on fuzzy clustering[D]. Jinan:Shandong University, 2015.
[14]	封雪, 李东新 . 基于数字图像处理的车牌字符分割方法[J].电子设计工程, 2014(22):185-187.
	Feng Xue, Li Dongxin . License plate character segmentation method based on digital image processing[J]. Electronic Design Engineering, 2014 ( 22):185-187.
[15]	杨秀泉 . 基于数字图像处理的车牌识别系统研究[D]. 西安:西安石油大学, 2014.
	Yang Xiuquan . Research on license plate recognition system based on digital image processing[D]. Xi’an:Xi’an Petroleum University, 2014.
[16]	马晓伟, 何向真, 于洪志 , 等. 基于数字图像处理的车牌定位与分割技术研究[J]. 西北民族大学学报:自然科学版, 2012,33(4):23-26.
	Ma Xiaowei, He Xiangzhen, Yu Hongzhi , et al. Research on license plate location and segmentation technology based on digital image processing[J]. Journal of Northwest University for Nationalities:Natural Science Edition, 2012,33(4):23-26.