改进的ViBe算法及其在交通视频处理中的应用

闵卫东; 郭晓光; 韩清

doi:10.3788/OPE.20172503.0806

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改进的ViBe算法及其在交通视频处理中的应用

信息科学 | 更新时间：2020-07-07

- 改进的ViBe算法及其在交通视频处理中的应用
- An improved ViBe algorithm and its application in traffic video processing
- 光学精密工程 2017年25卷第3期页码：806-811
- 作者机构：
  
  1.南昌大学信息工程学院, 南昌 330031
  2.天津工业大学计算机科学与软件学院, 天津 300387
- 作者简介：
  
  闵卫东 (1966－), 男, 江西会昌人, 博士, 教授, 博士生导师, 1989年、1991年、1995年于清华大学分别获得学士、硕士和博士学位, 1995年至2014年在加拿大Alberta大学和Corel等跨国公司从事研究工作, 主要从事图形图像处理、图形学、分布式系统、智慧城市等方面的研究。E-mail:minweidong@ncu.edu.cn MIN Wei-dong, E-mail:minweidong@ncu.edu.cn
  [ "郭晓光 (1992-), 男, 安徽舒城人, 硕士研究生, 2014年于天津工业大学获得学士学位, 主要从事视频图像处理研究。E-mail:gxg_tjpu@163.com" ]
- 基金信息：
  
  国家自然科学基金资助项目(61302127);江西省自然科学基金重大项目(20161ACB20004)
- DOI：10.3788/OPE.20172503.0806
  中图分类号： TP391.4
- 收稿日期：2016-12-21，
  
  录用日期：2017-1-15，
  
  纸质出版日期：2017-03-25
- 稿件说明：
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闵卫东, 郭晓光, 韩清. 改进的ViBe算法及其在交通视频处理中的应用[J]. 光学精密工程, 2017,25(3):806-811.

Wei-dong MIN, Xiao-guang GUO, Qing HAN. An improved ViBe algorithm and its application in traffic video processing[J]. Optics and precision engineering, 2017, 25(3): 806-811.
闵卫东, 郭晓光, 韩清. 改进的ViBe算法及其在交通视频处理中的应用[J]. 光学精密工程, 2017,25(3):806-811. DOI： 10.3788/OPE.20172503.0806.

Wei-dong MIN, Xiao-guang GUO, Qing HAN. An improved ViBe algorithm and its application in traffic video processing[J]. Optics and precision engineering, 2017, 25(3): 806-811. DOI： 10.3788/OPE.20172503.0806.

摘要

基于ViBe算法的运动目标检测具有很高的处理效率，但在复杂背景下也存在缺陷，比如不能有效抑制运动目标的残影和鬼影区域、易受噪音干扰，在交通视频的处理中更为明显。鉴于ViBe算法的这些不足，本文对ViBe原算法提出了改进，结合像素生命长度对鬼影或残影像素进行判断，利用二次更新策略提高消除速度。根据像素值变化引入最大类间方差法，将原有的固定像素阈值变为动态阈值，以提高交通视频中车辆目标检测的抗干扰能力。实验结果表明，在3组不同交通场景视频中，改进算法能够在较少帧数内消除目标的残影或者鬼影。对结果的量化分析也证明了改进算法由于应用了动态阈值，使目标检测的精准度和整体性都有所提高。

Abstract

Moving object detection based on the ViBe algorithm has high processing efficiency

but also some defects under complicated background

for example

it is unable to effectively suppress the ghost shadows and residual shadows of moving objects

vulnerable to noise

which is more apparent in processing of traffic videos. Subject to such deficiencies

the original ViBe algorithm was improved in the paper

as in to make judgment on pixel of ghost shadows and residual shadows by using life length matrix of pixel

to apply second update strategy to improve shadow elimination speed. According to changes of pixel value

OTSU method was introduced to transform the original fixed pixel threshold value into dynamic threshold and to promote the anti-jamming capability of vehicle objects detection contained in traffic videos. The results show that among the three groups of traffic scene video

the improved algorithm is able to eliminate the ghost shadows and residual shadows of moving objects within few frames. The quantitative analysis on results also proved the application of dynamic threshold in such improved algorithm could promote the accuracy and overall performance of object detection in traffic videos.

关键词

Keywords

references

MAHMASSANI, HANI S. Data-driven intelligent transportation systems: a survey [J]. IntelligentTransportation Systems, 2011, 12(4):1624-1639.

张仲瑜, 焦淑红.多特征融合的红外舰船目标检测方法[J].红外与激光工程, 2015, 44(S1): 29-34.

ZHANG ZH Y, JIAO SH H. Infrared ship target detection method based on multiple feature fusion [J]. Infrared and Laser Engineering , 2015, 44(S1): 29-34.(in Chinese)

ZHANG B, PERINA A, LI Z. Bounding multiple Gaussian uncertainty with application to object tracking [J]. International Journal of Computer Vision , 2016, 118(3):1-16.

LI W, YAO J, DONG T, et al .. Moving vehicle detection based on an improved inter-frame difference and a Gaussian model [C]. International Congress on Image and Signal Processing . IEEE, 2015.

赖丽君, 徐智勇, 张栩铫.应用于稳像系统中的改进梯度光流法[J].红外与激光工程, 2016, 45(4):273-279.

LAI L J, XU ZH Y, ZHANG X Y. Improved gradient optical flow for digital image stabilization [J]. Infrared and Laser Engineering , 2016, 45(4): 273-279.(in Chinese)

RAMYA P, RAJESWARI R. A modified frame difference method using correlation coefficient for background subtraction [J]. Procedia Computer Science, 2016, 93:478-485.

BARNICH O, DROOGENBROECK M. ViBe: a powerful random technique to estimate the background in video sequences [C]. IEEE International Conference on Acoustics, Speech and Signal Processing. Taipei: 2009, 945-948

赵光明, 韩光.基于融合帧间差的改进ViBe方法[J].计算机技术与发展, 2015(3):76-80.

ZHAO G M, HAN G. An improved ViBe method based on frame difference of fusion [J]. Computer Technology and Development , 2015(3):76-80. (in Chinese)

HUANG W, LIU L. The moving target detection algorithm based on the improved visual background extraction [J]. Infrared Physics and Technology , 2015, 71:518-525.

BARNICH O, DROOGENBROECK M V. ViBe: a universal background subtraction algorithm for video sequences [J]. IEEE Transactions on Image Processing , 2011, 20(6):1709-1724.

何志勇, 孙立宁, 陈立国. OTSU准则下分割阈值的快速计算[J].电子学报, 2013(2):267-272.

HE ZH Y, SUN L N, CHEN L G. Fast computation of threshold based on OTSU criterion [J]. Acta Electronica Sinica , 2013(2):267-272.(in Chinese)

ANDREA P, IVANA M. Detecting moving shadows:algorithms and evaluation [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence , 2003, 25(7): 918-923.

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