[1]陈利.基于深度学习的车牌识别系统设计[J].计算机技术与发展,2018,28(06):85-89.[doi:10.3969/ j. issn.1673-629X.2018.06.019]
　CHEN Li.Design of License Plate Recognition System Based on Deep Learning[J].,2018,28(06):85-89.[doi:10.3969/ j. issn.1673-629X.2018.06.019]
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基于深度学习的车牌识别系统设计()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
28
期数:
2018年06期
页码:
85-89
栏目:
智能、算法、系统工程
出版日期:
2018-06-10

文章信息/Info

Title:
Design of License Plate Recognition System Based on Deep Learning
文章编号:
1673-629X(2018)06-0085-05
作者:
陈利1   2
1. 西北大学 信息科学与技术学院,陕西 西安 710127;
2. 铜川职业技术学院 基础部,陕西 铜川 727031
Author(s):
CHEN Li 1   2
1. School of Information Science and Technology,Northwest University,Xi’an 710127,China;
2. Department of Basic Courses,Tongchuan Vocational and Technical College,Tongchuan 727031,China
关键词:
图像预处理; 车牌定位; 车牌字符分割; 车牌字符识别; Hausdorff 距离
Keywords:
image preprocessing; license plate location; license plate character segmentation; license plate character recognition; Hausdorff distance
分类号:
TP302.1
DOI:
10.3969/ j. issn.1673-629X.2018.06.019
文献标志码:
A
摘要:
随着国内机动车辆数目的不断增加,如何对众多的机动车进行有效管理已成为当前交通管理机构面临的主要问题。 利用深度学习技术,通过对车牌定位、车牌字符分割和车牌字符识别技术进行研究,提出了一种车牌识别原型系统方案。 在车牌预处理模块,通过图像灰度化处理等一系列操作,抑制了非车牌区域的噪声;在车牌定位模块,提出使用基于深度学习的目标检测方法对车牌进行定位,进行二值化、倾斜校正后使用垂直投影法分割出车牌字符,最后通过改进的Hausdorff 距离计算待识别图像与模板之间的相似程度,利用模板匹配的方法识别出车牌字符。 实验结果显示,该系统车牌识别准确率高。
Abstract:
With increasing of vehicles in domestic,how to effectively manage a large number of motor vehicles has become the main problem in the current traffic management institutions. In this paper,we propose a prototype system of license plate recognition through the research of license plate location,license plate character segmentation and recognition by using deep learning technology. In the plate preprocessing module,a series of operations,such as image grayscale processing,are used for denoising in the non-license plate area. In the plate location module,a target detection method based on deep learning is adopted. After the binarization and tilt correction,license plate characters are segmented by vertical projection. Finally,the similarity between the image and the template is calculated by the improved Hausdorff distance,and the license plate characters are recognized by the template matching method. The experiment shows that the accuracy of license plate recognition system is higher than others.

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更新日期/Last Update: 2018-08-16