|本期目录/Table of Contents|

[1]冯宇平,安雪美,孔祥茂.基于视频流的车牌识别研究及系统设计[J].工业仪表与自动化装置,2017,(01):32-36.
　FENG Yuping,AN Xuemei,KONG Xiangmao.Research on Vehicle License Plate Recognition and System Design Based on Video Stream[J].Industrial Instrumentation & Automation,2017,(01):32-36.
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基于视频流的车牌识别研究及系统设计

《工业仪表与自动化装置》[ISSN:1000-0682/CN:61-1121/TH]

卷:
期数:
2017年01期
页码:
32-36
栏目:
出版日期:
2017-02-15

文章信息/Info

Title:
Research on Vehicle License Plate Recognition and System Design Based on Video Stream
文章编号:
1000-0682（2017）01-0000-00
作者:
冯宇平; 安雪美; 孔祥茂
（青岛科技大学 自动化与电子工程学院，山东 青岛 266042）
Author(s):
FENG Yuping; AN Xuemei; KONG Xiangmao
(College of Automation and Electronic Engineering，Qingdao University of Science and Technology，Shandong Qingdao 266042， China)
关键词:
车牌识别; 车牌定位; 字符分割; 字符识别
Keywords:
license plate recognition;  license plate location;  character segmentation;  character recognition
分类号:
TP391
DOI:
-
文献标志码:
A
摘要:
该文深入研究从视频流中提取运动车辆进行车牌识别的问题，提出了一种车牌识别算法，根据该算法开发了基于MFC的视频流车牌识别可视化系统。算法采用三帧差分与背景消减相结合的方法提取含有运动车辆的关键帧，对关键帧进行灰度化，采用Sobel算子进行边缘检测，融合形态学处理对关键帧进行去噪，从而实现车牌的定位，用投影法结合字符特征对车牌字符进行精确分割，采用BP神经网络算法提取字符特征，输出字符识别结果，由此完成车牌字符识别。通过对50组不同的车辆视频进行检测识别，识别率(包含汉字)达到96%以上。
Abstract:
In this paper, the problem of license plate recognition by extracting vehicle license plate from the video stream is studied, and a license plate recognition algorithm based on which a visualization system of vehicle license plate recognition based on MFC is developed is presented. For this algorithm, three frames difference and background subtraction are applied to extract key frames containing moving vehicles. Then gray-scale of the key frames, edge detection using Sobel Operator, and fusion of morphological processing of key frames for denoising are carried out for location of license plate. Next, the characters of the license plate are segmented by the projection method combining with and the features of the characters and The BP neural network algorithm is used to extract the features of the characters and then character recognition results is output. Thereby, license plate characters are recognized. By recognizing 50 sets of different vehicle video, it was shown that recognition rate (including Chinese characters) is up to more than 96%.

参考文献/References:

[1] Samiul Azam, Md Monirul Islam. Automatic license plate detection in hazardous condition[C]. Journal of Visual Communication and Image Representation, 2016, 36(4): 172-186. [2] SL Chang, LS Chen, YC Chung, SW Chen. Automatic license plate recognition[C]. IEEE Transactions on Intelligent Transportation Systems, 2004, 27(10): 42-53. [3] 黄宝生，黄海波.车牌视频跟踪识别系统的设计[J].计算机应用技术(图形图像处理)， 2013，15(5): 192-232. [4] 高峰.基于车牌识别的车辆视频检索系统设计[D].北京:北京理工大学硕士论文，2015. [5] 李珊珊，李一民，郭真真.基于神经网络的分阶车牌字符识别算法研究[J].工业仪表与自动化装置，2016(2): 7-10. [6] ZHANG Xingwang, LIU Xiangui, ZHAO Jia. A Vehicle License Plate Recognition Method based on Neural Network[C].2010 IEEE International Conference on Granular Computing, 2010: 845-847. [7] 张弘.数字图像处理与分析[M].北京:机械工业出版社，2013: 1-130. [8] 毛星云，冷雪飞.OpenCV3编程入门[M].北京:电子工业出版社，2015:185-200.

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备注/Memo

备注/Memo:
收稿日期：2016-10-12 基金项目：山东省自然科学基金(ZR2015FL008、ZR2014FM013、ZR2014FL026)；山东省高等学校科技计划项目(J15LN39)；国家自然科学基金(61401244) 作者简介：冯宇平(1982)，女，吉林伊通人，博士，硕士生导师，中科院长春光学精密机械与物理研究所硕博连读并获得光学工程专业博士学位，主要从事图像数据的处理，配准拼接融合，人脸识别及信息物理系统等方面的研究工作。
更新日期/Last Update: 1900-01-01