广东工业大学学报 ›› 2013, Vol. 30 ›› Issue (1): 55-60.doi: 10.3969/j.issn.1007-7162.2013.01.010

• 综合研究 • 上一篇    下一篇

基于二次帧差背景提取的车辆追踪方法

陈泓屺,章云,刘国英   

  1. 广东工业大学 自动化学院,广东 广州 510006
  • 收稿日期:2012-05-25 出版日期:2013-03-30 发布日期:2013-03-30
  • 作者简介:陈泓屺(1986-),男,硕士研究生,主要研究方向为图像处理、模式识别.

Chen Hong-qi,Zhang Yun,Liu Guo-ying   

  1. School of Automation, Guangdong University of Technology, Guangzhou 510006,China
  • Received:2012-05-25 Online:2013-03-30 Published:2013-03-30

摘要: 针对智能交通系统对交通参数获取的实时性需求,利用背景的短时不变性,并结合帧差分法与背景差分法,提出一种运动车辆的追踪方法.该方法采用二次帧差法对背景快速提取,再对采用背景差分法获得的差分图像进行二值化,同时,为提高识别率对二值化图像进行了形态学操作,得到了较为完整的连通域.最后以帧间连通域的距离为依据,进行车辆追踪.实验结果表明,该方法具有良好的实时性和精确度以及鲁棒性,能够满足智能交通系统的实时需求.

关键词: 车辆追踪;背景提取;帧差分法;二次帧差背景提取法;背景差分法

Abstract: To satisfy the realtime demand for the traffic parameters in the Intelligent Transportation System, it proposed a new method by combining the framedifference method with the backgrounddifference method for vehicle tracking with the invariance property of the background in a short time. This method was used to complete a rapid background extraction by the method of twice framedifference, and the binary difference image was obtained by the method of backgrounddifference. Morphology operation was introduced to handle the binary image, which can improve the recognition rate to get a relatively complete connected domain. At last, vehicles were tracked, based on the distance between the connected domain of the close frames. Experimental results show that the scheme has good realtime and accuracy performance as well as robustness to meet the demand in the Intelligent Transportation System.

Key words: vehicle tracking; background extraction; framedifference; background extraction based on twice framedifference; background difference

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