计算机应用 ›› 2013, Vol. 33 ›› Issue (05): 1394-1400.DOI: 10.3724/SP.J.1087.2013.01394

• 多媒体处理技术 • 上一篇    下一篇

改进的混合高斯模型及阴影消除方法

陈雷1,张荣国1,胡静1,刘焜2   

  1. 1. 太原科技大学 计算机科学与技术学院,太原 030024
    2. 合肥工业大学 机械与汽车工程学院,合肥 230009
  • 收稿日期:2012-10-24 修回日期:2012-12-11 出版日期:2013-05-01 发布日期:2013-05-08
  • 通讯作者: 张荣国
  • 作者简介:陈雷(1981-),男,山东菏泽人,硕士,主要研究方向:图像处理、计算机视觉;张荣国(1964-),男,山西太原人,教授,博士,主要研究方向:计算机图形学与辅助设计、图形图像处理、模式识别;胡静(1977-),女,山西大同人,副教授,硕士,主要研究方向:图形图像处理、优化算法;刘焜(1963-),男,陕西汉中人,教授,博士,主要研究方向:现代设计方法。
  • 基金资助:

    国家自然科学基金资助项目(51075113);太原科技大学博士基金资助项目(20122015)

Improved Gaussian mixture model and shadow elimination method

CHEN Lei1,ZHANG Rongguo1,HU Jing1,LIU Kun2   

  1. 1. School of Computer Science and Technology,Taiyuan University of Science and Technology, Taiyuan Shanxi 030024, China
    2. School of Mechanical and Automotive Engineering, Hefei University of Technology, Hefei Anhui 230009,China
  • Received:2012-10-24 Revised:2012-12-11 Online:2013-05-08 Published:2013-05-01
  • Contact: ZHANG Rongguo

摘要: 为了有效减少运动目标检测中混合高斯模型的计算量和提高阴影消除的准确性,提出了一种选择性地更新混合高斯模型和基于亮度变化消除阴影的方法。首先,在各个高斯分布进行更新之前,先将其权值与不属于背景的高斯分布的比重进行比较,若前者较大,则此高斯分布不更新,反之则更新;然后,在阴影消除时,将亮度的变化程度作为阴影检测阈值的一个因子,以使其随亮度变化自适应地做出调整。最后,将该方法与传统方法在室内外视频条件下进行了实验对比,结果表明该方法的计算时间约为传统方法的1/3,阴影消除更加准确。

关键词: 运动目标检测, 自适应, 背景减除, 阈值, 混合高斯模型, 阴影消除

Abstract: To reduce the computation of Gauss mixture model effectively and improve the accuracy of shadow elimination in moving object detection, an algorithm which updated the model selectively and eliminated the shadow by the change of brightness was proposed. Firstly, the weight of the Gauss distribution and the rate of those that did not belong to the background were compared before updating the Gauss distribution, if the former was larger, then did not update it, otherwise, updated it; Secondly, the range of brightness change was chosen to be a threshold factor of shadow detection, so that the threshold could be adjusted adaptively according to the change of brightness. Finally, compared this algorithm with the traditional ones through experiments on indoor and outdoor videos, the experimental results show that the time consumption of the algorithm is about one-third of the traditional ones, the accuracy of shadow eliminating is improved and the efficiency of the algorithm is confirmed.

Key words: moving object detection, adaptive, background subtraction, threshold, Gaussian mixture model, shadow elimination

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