An Approach to Instantly Detecting Fake Plates based on Large-scale ANPR Data

摘要：

　　Traditional methods of detecting fake plates are mostly inefficient.They usually require lots of investments in advance.These methods cannot fully play potentials of ANPR(Automatic Number Plate Recognition) data and utilize them to detect fake plates quickly.In this paper, we propose a method,called as FP-Detector, to instantly detect fake plates through parallel analyzing the historical large-scale ANPR data with MapReduce.The main contributions include: we design a partition strategy, which can fully use the features of ANPR and maintain balances among different nodes.In addition, we also give a criterion of judging fake plates through analyzing spatiotemporal contradiction of plate information.Finally, we apply our method on a real large-scale data set and compare the performance of our method with default blocking strategy of MapReduce.The experiment results show the effectiveness of our method.

关键词： Fake Plates Blocking Spatio-temporal Contradiction Load Balance MapReduce

作者: Yue Li Chen Liu

作者单位: Beijing Key Laboratory on Integration and Analysis of Large-scale Stream Data North China University of Technology Beijing, China

会议类型: 国际会议

会议名称: The 12th Web Information System and Application Conference第十二届全国Web信息系统及其应用学术会议(WISA2015)、全国第十次语义Web 与本体论学术研讨会(SWON2015)、全国第九次电子政务技术及应用学术研讨会(EGTA2015)

会议地点: 济南

会议语种:英文

页码: 287-292

在线出版日期: 2015-09-11（万方平台首次上网日期，不代表论文的发表时间）