基于车牌识别大数据的伴随车辆组发现方法

doi:10.11772/j.issn.1001-9081.2015.11.3203

计算机应用 ›› 2015, Vol. 35 ›› Issue (11): 3203-3207.DOI: 10.11772/j.issn.1001-9081.2015.11.3203

• 2015年全国开放式分布与并行计算学术年会(DPCS 2015)论文 • 上一篇下一篇

基于车牌识别大数据的伴随车辆组发现方法

曹波^1,2, 韩燕波^1,2, 王桂玲²

1. 山东科技大学信息科学与工程学院, 山东青岛 266590;
2. 大规模流数据集成与分析技术北京市重点实验室(北方工业大学), 北京 100144

收稿日期:2015-06-17 修回日期:2015-07-28 发布日期:2015-11-13
通讯作者: 曹波(1990-),男,山东莱芜人,硕士研究生,主要研究方向:云计算、大规模数据集成.
作者简介:韩燕波(1962-),男,河北承德人,教授,博士生导师,博士,CCF高级会员,主要研究方向:云计算、互联网服务; 王桂玲(1978-),女,山东菏泽人,副教授,博士,CCF会员,主要研究方向:数据集成、服务组合.
基金资助:
北京市属高等学校创新团队建设与教师职业发展计划项目(IDHT20130502);北京市自然科学基金重点项目(4131001).

Discovery method of travelling companions based on big data of license plate recognition

CAO Bo^1,2, HAN Yanbo^1,2, WANG Guiling²

1. College of Information Science and Engineering, Shandong University of Science and Technology, Qingdao Shandong 266590, China;
2. Beijing Key Laboratory on Integration and Analysis of Large-scale Stream Data (North China University of Technology), Beijing 100144, China

Received:2015-06-17 Revised:2015-07-28 Published:2015-11-13

摘要/Abstract

摘要： 基于对车牌识别大数据的处理与分析,可以完成伴随车辆组的发现,在涉案车辆追踪等方面具有广泛的应用.然而当前单一机器模式下伴随车辆组发现算法存在时间和空间上处理性能低下等问题.针对此问题,提出了一种伴随车辆组发现方法——FP-DTC方法.该方法将传统的FP-Growth算法利用分布式处理框架Spark进行了并行化,并作了相应的改进和优化来更加高效地发现伴随车辆组.实验结果的分析表明,提出的方法能够很好地解决车牌识别大数据上的伴随车辆组发现问题,性能相比采用同样方法的Hadoop实现提升了近4倍.

关键词: 智能交通系统, 车牌识别, 伴随车辆组, FP-Growth算法, Spark并行框架

Abstract: The discovery of travelling companions based on processing and analysis of the license plate recognition big data has become widely used in many aspects such as the involved vehicle tracking. However, discovery algorithms of travelling companions have poor performance in single machine mode no matter in time and space. To solve this problem, a discovery method of travelling companions named FP-DTC was proposed. This method based on the algorithm of FP-Growth was parallelled by the distributed processing framework-Spark, and had made some improvement and optimization to discover the travelling companions more efficiently. The experimental results show that, this method performs well on the discovery of travelling companions, and achieves an increase of nearly four times than the same algorithm with Hadoop.

Key words: Intelligence Transportation System (ITS), license plate recognition, travelling companions, FP-Growth algorithm, Spark parallel framework

中图分类号:

TP391.41

曹波, 韩燕波, 王桂玲. 基于车牌识别大数据的伴随车辆组发现方法[J]. 计算机应用, 2015, 35(11): 3203-3207.

CAO Bo, HAN Yanbo, WANG Guiling. Discovery method of travelling companions based on big data of license plate recognition[J]. Journal of Computer Applications, 2015, 35(11): 3203-3207.

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基于车牌识别大数据的伴随车辆组发现方法

Discovery method of travelling companions based on big data of license plate recognition

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