计算机应用 ›› 2015, Vol. 35 ›› Issue (6): 1739-1743.DOI: 10.11772/j.issn.1001-9081.2015.06.1739

• 虚拟现实与数字媒体 • 上一篇    下一篇

基于ViBe的室外动态背景闪烁像素噪声消除方法

周晓, 赵锋, 朱艳林   

  1. 浙江工业大学 信息工程学院, 杭州 310023
  • 收稿日期:2014-12-23 修回日期:2015-03-24 发布日期:2015-06-12
  • 通讯作者: 周晓(1972-),男,浙江永康人,副教授,博士,主要研究方向:嵌入式系统、计算机视觉;zx@zjut.edu.cn
  • 作者简介:赵锋(1990-),男,浙江杭州人,硕士研究生,主要研究方向:嵌入式系统、计算机视觉;朱艳林(1988-),男,湖北武汉人,硕士研究生,主要研究方向:计算机视觉、网络化控制与监控。

Noise-suppression method for flicker pixels in dynamic outdoor scenes based on ViBe

ZHOU Xiao, ZHAO Feng, ZHU Yanlin   

  1. College of Information Engineering, Zhejiang University of Technology, Hangzhou Zhejiang 310023, China
  • Received:2014-12-23 Revised:2015-03-24 Published:2015-06-12

摘要:

针对使用视觉背景提取(ViBe)模型在室外动态背景下进行移动目标检测时存在不规则闪烁像素点对前景检测结果造成干扰的问题,提出一种基于视觉背景提取算法的闪烁像素噪声消除方法。在背景模型建立阶段设定背景模型样本标准差阈值,约束背景模型的采样值范围以提高背景模型准确性。在前景检测阶段引入自适应检测阈值提高前景物体检测精度,在背景模型更新过程中对图像边缘背景像素点进行边缘抑制以阻止错误背景样本值更新到背景模型。在此基础上,结合形态学操作修复连通域,提高前景图像的完整性。最后选取多个视频序列将该方法与原始ViBe算法、形态学改进方法的检测结果进行对比。实验结果表明,该方法能有效消除闪烁像素噪声对前景检测造成的影响,获取更精确的前景图像。

关键词: 移动目标检测, 视觉背景提取算法, 自适应检测阈值, 边缘抑制, 闪烁像素噪声

Abstract:

Visual Background extractor (ViBe)model for moving target detection cannot avoid interference caused by irregular flicker pixels noise in dynamic outdoor scenes. In order to solve the issue, a flicker pixels noise-suppression method based on ViBe model algorithm was proposed. In the initial stage of background model, a fixed standard deviation of background model samples was used as the threshold value to limit the range of background model samples and get suitable background model samples for each pixel. In the foreground detection stage, an adaptive detection threshold was applied to improve the accuracy of detection result. Edge inhibition of image edge background pixels was executed to avoid error background sample values updating to the background model in the background model update process. On the basis of above, morphological operation was added to fix connected components to get more complete foreground images. Finally, the proposed method was compared with the original ViBe algorithm and the ViBe's improvement with morphology post-processing on the results of multiple video sequences. The experimental results show that the flicker pixels noise-suppression method can suppress flicker pixels noise effectively and get more accurate results.

Key words: moving object detection, Visual Background extractor (ViBe) algorithm, adaptive detection threshold, edge inhibition, flicker pixels noise

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