基于嵌入式车流量实时检测算法研究与实现

马永杰; 宋晓凤; 李雪燕; 刘姣姣

doi:10.3788/YJYXS20183309.0787

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基于嵌入式车流量实时检测算法研究与实现

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- 基于嵌入式车流量实时检测算法研究与实现
- Research and implementation of real-time vehicle flow detection algorithm based on embedded system
- 液晶与显示 2018年33卷第9期页码：787-792
- 作者机构：
  
  西北师范大学物理与电子工程学院, 甘肃兰州 730070
- 作者简介：
  
  [ "马永杰(1967-), 男, 甘肃灵台人, 博士, 教授, 硕士生导师, 主要从事进化算法、测控技术及应用方面的研究。E-mail:myjmyj@nwnu.edu.cn" ]
- 基金信息：
  
  国家自然科学基金(41461078);National Natural Science Foundation of China(41461078)
- DOI：10.3788/YJYXS20183309.0787
  中图分类号： TP29
- 收稿日期：2018-03-29，
  
  录用日期：2018-6-8，
  
  纸质出版日期：2018-09-05
- 稿件说明：
移动端阅览
马永杰, 宋晓凤, 李雪燕, 等. 基于嵌入式车流量实时检测算法研究与实现[J]. 液晶与显示, 2018,33(9):787-792.

Yong-jie MA, Xiao-feng SONG, Xue-yan LI, et al. Research and implementation of real-time vehicle flow detection algorithm based on embedded system[J]. Chinese journal of liquid crystals and displays, 2018, 33(9): 787-792.
马永杰, 宋晓凤, 李雪燕, 等. 基于嵌入式车流量实时检测算法研究与实现[J]. 液晶与显示, 2018,33(9):787-792. DOI： 10.3788/YJYXS20183309.0787.

Yong-jie MA, Xiao-feng SONG, Xue-yan LI, et al. Research and implementation of real-time vehicle flow detection algorithm based on embedded system[J]. Chinese journal of liquid crystals and displays, 2018, 33(9): 787-792. DOI： 10.3788/YJYXS20183309.0787.

摘要

针对道路现场实时车流量检测问题，提出了一种改进的帧间差分法的运动车辆检测算法，并将该检测算法成功移植到了嵌入式系统上。将帧间差分法与采用长度、宽度、面积筛选轮廓及用质心距离的车辆跟踪算法结合，实现运动车辆的检测；将U-Boot引导程序、Linux内核、Yaffs2文件系统和检测算法移植到S3C6410上，通过摄像头实时采集交通视频，检测结果由触摸屏显示。复杂交通场景的实时测试结果表明，本系统的检测时间为0.298秒/帧，准确率超过88%，基本能够实现在道路现场的车流量实时检测。

Abstract

Aiming at the problem of real-time traffic flow in the road

an improved algorithm for moving vehicle detection based on frame subtraction was proposed

and the algorithm was successfully transplanted into the embedded system. The Frame subtraction was combined with vehicle tracking algorithm using length

width

area selection contour and centroid distance to realize the detection of moving vehicle. The U-boot program

Linux kernel

Yaffs2 file system and detection algorithm were transplanted to the S3C6410

and the traffic video was collected through the camera

and the detection results were displayed by the touch-screen. The real-time test results of complex traffic scene show that the detection time of the system is 0.298 seconds/frame

and the accuracy rate is over 88%

which can basically realize the real-time vehicle flow detection in the road scene.

关键词

Keywords

references

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