基于颜色布局描述子的改进ViBe算法

doi:10.11772/j.issn.1001-9081.2019071208

计算机应用 ›› 2020, Vol. 40 ›› Issue (3): 812-818.DOI: 10.11772/j.issn.1001-9081.2019071208

• 虚拟现实与多媒体计算 • 上一篇下一篇

基于颜色布局描述子的改进ViBe算法

王彤¹, 王巍^1,2,3, 崔益豪¹, 朱天宇¹

1. 河北工程大学信息与电气工程学院, 河北邯郸 056038;
2. 物联网技术应用教育部工程研究中心(江南大学), 江苏无锡 214122;
3. 江南大学物联网工程学院, 江苏无锡 214122

收稿日期:2019-07-11 修回日期:2019-08-22 出版日期:2020-03-10 发布日期:2019-09-19
通讯作者: 王巍
作者简介:王彤(1995-),女,河北邯郸人,硕士研究生,主要研究方向:人工智能、图像处理;王巍(1983-),男,河北邯郸人,副教授,博士,CCF会员,主要研究方向:公共安全物联网、隐式人机交互;崔益豪(1994-),男,河南洛阳人,硕士研究生,主要研究方向:群智能算法、人工智能、嵌入式系统;朱天宇(1996-),男,江苏徐州人,硕士研究生,主要研究方向:无人机、无人驾驶。
基金资助:
国家重点研发计划项目（2018YFF0301004）；国家自然科学基金资助项目（61802107）；教育部-中国移动科研基金资助项目（MCM20170204）；江苏省博士后科研资助计划项目（1601085C）。

Improved ViBe algorithm based on color layout descriptor

WANG Tong¹, WANG Wei^1,2,3, CUI Yihao¹, ZHU Tianyu¹

1. College of Information and Electrical Engineering, Hebei University of Engineering, Handan Hebei 056038, China;
2. Engineering Research Center of Internet of Things Technology Applications, Ministry of Education(Jiangnan University), Wuxi Jiangsu 214122, China;
3. School of Internet of Things Engineering, Jiangnan University, Wuxi Jiangsu 214122, China

Received:2019-07-11 Revised:2019-08-22 Online:2020-03-10 Published:2019-09-19
Supported by:
This work is partially supported by the National Key R&D Program of China (2018YFF0301004), the National Natural Science Foundation of China (61802107), the Ministry of Education-China Mobile Research Fund Project (MCM20170204), the Jiangsu Postdoctoral Research Support Program (1601085C).

摘要/Abstract

摘要： 针对ViBe算法在检测运动目标时会有“鬼影”产生和在动态背景下会对目标检测过程中产生干扰造成运动目标误检的问题，结合颜色布局描述子（CLD）提取关键帧进行三帧差分、形态学后处理的技术，提出一种改进的ViBe算法。首先，通过CLD提取视频关键帧图像；然后，将所选取关键帧图像进行三帧差分，通过差分结果将含有运动目标的背景模型进行填充，得到真实的背景图像，再对运动目标进行检测，以达到消除鬼影的目的；最后，在背景模型更新的阶段加入自适应阈值的形态学处理技术，消除动态背景模型中的干扰信息。实验结果表明，所提算法在运动目标检测时在避免鬼影、抗动态背景干扰等方面表现出优越性，在相似度量阈值选取为0.67到0.72时，所提算法的准确率最高可以达到99.4%，可以理想地检测出运动目标的位置信息。

关键词: 运动目标检测, ViBe, 关键帧, 三帧差, 颜色布局描述子, 鬼影

Abstract: In view of the problem that ViBe (Visual Background extractor) algorithm sometimes produces “ghost” when detecting moving targets and the misdetection problem of moving targets caused by the interference produced by the algorithm in the target detection with dynamic background, an improved ViBe algorithm was proposed based on the techniques of three frame differencing and morphological post-processing carried on the key frames extracted by Color Layout Descriptor (CLD). Firstly, the video key frame images were extracted by CLD. Secondly, three frame differencing was performed on the selected key frame images. The background model containing the moving target was filled by the difference results, obtaining the real background image. Thirdly, the moving target was detected, so as to eliminate the “ghost”. Finally, the morphological processing technique with adaptive threshold was added in the updating stage of background model to eliminate the interference information in the dynamic background model. The experimental results show that the proposed algorithm has superiority in avoiding ghost and anti-dynamic background interference in moving target detection, and when the similar measurement threshold is selected from 0.67 to 0.72, the accuracy of the algorithm can be as high as 99.4%, indicating that the algorithm can ideally detect the position information of the moving target.

Key words: moving target detection, ViBe (Visual Background extractor), key frame, three frame differencing, Color Layout Descriptor (CLD), ghost

中图分类号:

TP391.41

王彤, 王巍, 崔益豪, 朱天宇. 基于颜色布局描述子的改进ViBe算法[J]. 计算机应用, 2020, 40(3): 812-818.

WANG Tong, WANG Wei, CUI Yihao, ZHU Tianyu. Improved ViBe algorithm based on color layout descriptor[J]. Journal of Computer Applications, 2020, 40(3): 812-818.

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基于颜色布局描述子的改进ViBe算法

Improved ViBe algorithm based on color layout descriptor

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