Pattern recognition method for license plate character based on multilevel RBF network

doi:10.3778/j.issn.1002-8331.2008.30.065

Computer Engineering and Applications ›› 2008, Vol. 44 ›› Issue (30): 213-216.DOI: 10.3778/j.issn.1002-8331.2008.30.065

• 工程与应用 • Previous Articles Next Articles

Pattern recognition method for license plate character based on multilevel RBF network

LI Meng-xin^1,2,WU Cheng-dong¹,XIA Xing-hua²

1.School of Information Science & Engineering，Northeastern University，Shenyang 110004，China
2.School of Information and Control Engineering，Shenyang Jianzhu University，Shenyang 110168，China

Received:2008-06-30 Revised:2008-08-01 Online:2008-10-21 Published:2008-10-21
Contact: LI Meng-xin

一种基于分级RBF网络的车牌字符识别方法

李孟歆^1,2,吴成东¹,夏兴华²

1.东北大学信息科学与工程学院，沈阳 110004
2.沈阳建筑大学信息与控制工程学院，沈阳 110168

通讯作者: 李孟歆

Abstract

Abstract: A new recognition algorithm for license plate character based on multi-level RBF network is proposed.Two-level RBF network is adopted.According to recognition results from one-level network and the confidence levels，recognition distribution table is built，and two-level network is accordingly designed.As a result，12 two-level sub-networks are formed.A large amount of samples are used for system test.Overall recognition accuracy is 85.4%.Through contrastive research，the method presented is proved to be effective and advanced.

Key words: license plate recognition, Radial Basis Function（RBF） network, two-level network, recognition accuracy

摘要： 提出了一种基于分级RBF神经网络的车牌字符识别方法，采用两级RBF神经网络结构，由一级网络识别后，根据识别结果和置信度，建立识别分布图，进行二级网络设计，确定了12个二级子网。RBF网络中自动确定隐层神经元数，无需实验调整。用大量样本对系统进行测试，车牌整体识别率达到了85.4%，通过对比性研究，验证了该方法的有效性和先进性。

关键词: 车牌识别, 径向基函数（RBF）网络, 二级网络, 识别率

LI Meng-xin^1,2,WU Cheng-dong¹,XIA Xing-hua². Pattern recognition method for license plate character based on multilevel RBF network[J]. Computer Engineering and Applications, 2008, 44(30): 213-216.

李孟歆^1,2,吴成东¹,夏兴华². 一种基于分级RBF网络的车牌字符识别方法[J]. 计算机工程与应用, 2008, 44(30): 213-216.

[1]	WANG Qiaoyue, CHEN Shuyue. Defogging Algorithm Based on Color Transfer and Regularization Constraints of License Plate Images [J]. Computer Engineering and Applications, 2021, 57(14): 217-222.
[2]	SONG Lili, LI Bin, ZHAO Junya, LIU Guofeng. Normality Resampling of Improved Metric Learning Method for Person Re-Identification [J]. Computer Engineering and Applications, 2020, 56(8): 158-165.
[3]	ZHANG Yanliang, LU Bing, JIANG Hanxiao, HONG Xiaopeng, ZHAO Guoying, ZHANG Weitao. Study on Investigating Correlation Between Categories of Micro-expression and Corresponded Regions [J]. Computer Engineering and Applications, 2020, 56(19): 146-151.
[4]	ZENG Tian, YANG Degang. Modeling and Application of Self Recursive RBF Network with PSO Algorithm [J]. Computer Engineering and Applications, 2019, 55(13): 172-177.
[5]	ZHAO Ying1, GENG Xiulin1, LI Qi1, JIANG Guangqi1, GU Yu1, 2. Study on dynamic image recognition in visual prosthesis [J]. Computer Engineering and Applications, 2018, 54(23): 162-169.
[6]	LI Yan1, ZHANG Hongbo2, SHI Lianying3. SIFT matching based method for license plate recognition [J]. Computer Engineering and Applications, 2016, 52(12): 194-200.
[7]	ZHANG Xulan. Optimized character recognition algorithm based on BP artificial neural network [J]. Computer Engineering and Applications, 2012, 48(35): 182-185.
[8]	MU Lijuan1, JI Yan2. New model of neighborhood used in segmentation of vehicle plate [J]. Computer Engineering and Applications, 2012, 48(19): 191-196.
[9]	LI Yucheng，YANG Guangming，WANG Mushu. Study of key technology in license plate recognition system [J]. Computer Engineering and Applications, 2011, 47(27): 180-184.
[10]	DENG Wei，WEI Yingmei，ZHANG Yougen. Personalized facial cartoon generation using image deformation [J]. Computer Engineering and Applications, 2011, 47(24): 132-135.
[11]	HE Zhaocheng，SHE Xiwei，YU Wenjin，YANG Wenchen. Method for multiple feature extraction of characters and application in vehicle license plate recognition [J]. Computer Engineering and Applications, 2011, 47(23): 228-231.
[12]	CHEN Bei,CAO Wen-lun,ZHANG Hong-cai. Research on multi-vehicle license plate location under complex background [J]. Computer Engineering and Applications, 2009, 45(17): 228-230.
[13]	WANG Jia,YU Jun-qi,GUO Chun-yan. Evaluation of water environmental quality using rough set—RBF network [J]. Computer Engineering and Applications, 2009, 45(13): 237-239.
[14]	ZHU Jun-mei,CHEN Shao-ping. Vehicle license plate location and segmentation in LPR system [J]. Computer Engineering and Applications, 2008, 44(14): 198-201.
[15]	SU Mei-juan,DENG Wei. Differential Evolution Orthogonal Least Square（DEOLS） algorithm for RBF network [J]. Computer Engineering and Applications, 2007, 43(35): 46-48.

Pattern recognition method for license plate character based on multilevel RBF network

一种基于分级RBF网络的车牌字符识别方法

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics