吉林大学学报(工学版) ›› 2015, Vol. 45 ›› Issue (2): 639-644.doi: 10.13229/j.cnki.jdxbgxb201502045

• 论文 • 上一篇    下一篇

基于层次策略的新型快速车牌定位方法

黄继鹏1，孙露1，乔双1，孙佳宁2   

  1. 1.东北师范大学 物理学院，长春 130024；
    2.东北师范大学 数学与统计学院，长春 130024
  • 收稿日期:2013-07-01 出版日期:2015-04-01 发布日期:2015-04-01
  • 通讯作者: 乔双(1963)，男，教授， 博士.研究方向:数字图像处理，核技术及应用.E-mail:qiaos810@nenu.edu.cn
  • 作者简介:黄继鹏(1984)，男，讲师，博士.研究方向:数字图像处理，核技术及应用.E-mail:huangjp848@nenu.edu.cn
  • 基金资助:
    国家自然科学基金项目(11275046，11305034)；吉林省科技发展计划项目(20150520084JH)；中央高校基本科研业务费专项项目(12QNJJ009).

Novel fast license plate location method based on hierarchical strategy

HUANG Ji-peng1,SUN Lu1,QIAO Shuang1,SUN Jia-ning2   

  1. 1.School of Physics, Northeast Normal University,Changchun 130024,China;
    2.School of Mathematics and Statistics, Northeast Normal University,Changchun 130024,China
  • Received:2013-07-01 Online:2015-04-01 Published:2015-04-01

RICH HTML

0   

PDF (PC)

322

摘要： 介绍了一种新型的基于层次策略的局部区域检测技术，提取了所有满足候选检测条件的局部兴趣区域。在此基础上，进行梯度增强、冗余边缘去除和车牌分割等精确定位操作。实验结果表明:本文方法对于克服环境噪声具有很强的鲁棒性，实现了高精度的车牌实时定位。

关键词: 计算机应用, 车牌定位, 层次策略, 梯度增强, 兴趣区域

Abstract: A novel search strategy for local region based on hierarchical region detection is proposed. All local regions of interest satisfying candidate detection condition are extracted using this strategy. Then the fine plate location, including gradient enhancement, redundant edge removing and plate segmentation, is performed sequentially. Experiments results show that the proposed method possesses strong robustness to environmental noise and provides high accuracy of real-time license plate location.

Key words: computer application, license plate location, hierarchical strategy, gradient enhancement, region of interest

中图分类号: 

  • TP391.4
[1] Rami A, Subhash C. License plate localization based on a probabilistic model[J]. Machine Vision and Applications, 2010,21(3): 319-330.
[2] Bai H, Liu C. A hybrid license plate extraction method based on edge statistics and morphology[C]∥Proceedings of the 17th International Conference on Pattern Recognition. Cambridge, UK:IEEE, 2004:831-834.

[3] Duan T D, Du T L H, Phuoc T V, et al. Building an automatic vehicle license-plate recognition system[C]∥The 3rd International Conference on Computer Science,Can Tho,Vietnam,2005:59-63.
[4] Yanamura Y, Goto M, Nishiyama D, et al. Extraction and tracking of the license plate using Hough transform and voted block matching[C]∥Proceedings of Intelligent Vehicles Symposium. Columbus. USA: IEEE, 2003:243-246.
[5] Wang Y R, Lin W H, Horng S J. A sliding window technique for efficient license plate localization based on discrete wavelet transform[J]. Expert Systems with Applications, 2011, 38(4): 3142-3146.
[6] Wen W, Huang X, Yang L, et al. Vehicle license plate location method based-on wavelet transform[C]∥Proceedings of International Joint Conference on Computational Sciences and Optimization. Hainan, CHN: IEEE, 2009:381-384.
[7] Anagnostopoulos C, Anagnostopoulos I, Kayafas E,et al. A license plate recognition system for intelligent transportation system applications[J]. IEEE Transaction on Intelligent Transportation Systems, 2006, 7(3): 377-392.
[8] Zunino R, Rovetta S. Vector quantization for license -plate location and image coding[J]. IEEE Transaction on Industrial Electronics, 2000, 47 (1): 159-167.
[9] Ming G H, Harvey A L, Danelutti P. Car number plate detection with edge image improvement[C]∥Proceedings of the 4th International Symposium on Signal Processing and Its Applications. GoldCoast AUS: IEEE, 1996:389-392.
[10] Miao L. License plate detection algorithm based on nearest neighbor chains[J]. Acta Automatica Sinica, 2011, 37 (10):1272-1279.
[11] Zhang H, Jia W, He X,et al. Learning-based license plate detection using global and local features[C]∥Proceedings of the 18th International Conference on Pattern Recognition. Hong Kong, CHN: IEEE, 2006: 1102-1105.
[12] Broumandnia A, Fathy M. Application of pattern recognition for Farsi license plate recognition[J]. International Journal on Graphics, Vision and Image Processing, 2005, 5(2):25-31.
[13] Zheng D, Zhao Y, Wang J. An efficient method of license plate location[J]. Pattern Recognition Letters, 2005, 26(15): 2431-2438.
[1] 刘富,宗宇轩,康冰,张益萌,林彩霞,赵宏伟. 基于优化纹理特征的手背静脉识别系统[J]. 吉林大学学报(工学版), 2018, 48(6): 1844-1850.
[2] 王利民,刘洋,孙铭会,李美慧. 基于Markov blanket的无约束型K阶贝叶斯集成分类模型[J]. 吉林大学学报(工学版), 2018, 48(6): 1851-1858.
[3] 金顺福,王宝帅,郝闪闪,贾晓光,霍占强. 基于备用虚拟机同步休眠的云数据中心节能策略及性能[J]. 吉林大学学报(工学版), 2018, 48(6): 1859-1866.
[4] 赵东,孙明玉,朱金龙,于繁华,刘光洁,陈慧灵. 结合粒子群和单纯形的改进飞蛾优化算法[J]. 吉林大学学报(工学版), 2018, 48(6): 1867-1872.
[5] 刘恩泽,吴文福. 基于机器视觉的农作物表面多特征决策融合病变判断算法[J]. 吉林大学学报(工学版), 2018, 48(6): 1873-1878.
[6] 欧阳丹彤, 范琪. 子句级别语境感知的开放信息抽取方法[J]. 吉林大学学报(工学版), 2018, 48(5): 1563-1570.
[7] 刘富, 兰旭腾, 侯涛, 康冰, 刘云, 林彩霞. 基于优化k-mer频率的宏基因组聚类方法[J]. 吉林大学学报(工学版), 2018, 48(5): 1593-1599.
[8] 桂春, 黄旺星. 基于改进的标签传播算法的网络聚类方法[J]. 吉林大学学报(工学版), 2018, 48(5): 1600-1605.
[9] 刘元宁, 刘帅, 朱晓冬, 陈一浩, 郑少阁, 沈椿壮. 基于高斯拉普拉斯算子与自适应优化伽柏滤波的虹膜识别[J]. 吉林大学学报(工学版), 2018, 48(5): 1606-1613.
[10] 车翔玖, 王利, 郭晓新. 基于多尺度特征融合的边界检测算法[J]. 吉林大学学报(工学版), 2018, 48(5): 1621-1628.
[11] 赵宏伟, 刘宇琦, 董立岩, 王玉, 刘陪. 智能交通混合动态路径优化算法[J]. 吉林大学学报(工学版), 2018, 48(4): 1214-1223.
[12] 黄辉, 冯西安, 魏燕, 许驰, 陈慧灵. 基于增强核极限学习机的专业选择智能系统[J]. 吉林大学学报(工学版), 2018, 48(4): 1224-1230.
[13] 傅文博, 张杰, 陈永乐. 物联网环境下抵抗路由欺骗攻击的网络拓扑发现算法[J]. 吉林大学学报(工学版), 2018, 48(4): 1231-1236.
[14] 曹洁, 苏哲, 李晓旭. 基于Corr-LDA模型的图像标注方法[J]. 吉林大学学报(工学版), 2018, 48(4): 1237-1243.
[15] 侯永宏, 王利伟, 邢家明. 基于HTTP的动态自适应流媒体传输算法[J]. 吉林大学学报(工学版), 2018, 48(4): 1244-1253.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
版权所有 © 《吉林大学学报(工学版)》编辑部
地址：长春市人民大街5988号　电话：+86-431-85095297　传真：+86-431-85094074　E-mail: xbgxb@jlu.edu.cn
本系统由北京玛格泰克科技发展有限公司设计开发