基于YCbCr的自适应混合高斯模型背景建模

J4 ›› 2015, Vol. 37 ›› Issue (01): 152-156.

基于YCbCr的自适应混合高斯模型背景建模

黄玉，殷苌茗，周书仁

(长沙理工大学计算机与通信工程学院，湖南长沙 410004)

收稿日期:2013-05-28 修回日期:2013-08-26 出版日期:2015-01-25 发布日期:2015-01-25
基金资助:
湖南省自然科学基金资助项目（12JJ6057）；湖南省教育厅资助科研项目（13B132）；长沙市科技计划资助项目（K120301511）

An adaptive MoG background modeling based on YCbCr

HUANG Yu,YIN Changming,ZHOU Shuren

(School of Computer and Communication Engineering,Changsha University of Science and Technology,Changsha 410004,China)

Received:2013-05-28 Revised:2013-08-26 Online:2015-01-25 Published:2015-01-25

摘要/Abstract

摘要：

混合高斯模型是最常用的背景建模方法之一，但是它的精确度是以耗时为代价的，且它在RGB颜色空间进行背景建模时，对噪声的处理效果一般。因此，对混合高斯模型进行改进，提出了一种基于YCbCr的自适应混合高斯模型背景建模方法。首先，将建模颜色空间从RGB转换到YCbCr；然后，采用自适应选择策略来确定混合高斯模型的高斯成分个数；最后，将高斯成分按照关键字的值进行排序，以确定背景模型。将提出的建模方法应用于运动目标检测，实验结果表明，提出的方法与混合高斯模型背景建模相比，运动目标检测的检测结果更准确，耗时更少。

关键词: 背景建模, 混合高斯模型, YCbCr颜色空间, 自适应选择策略

Abstract:

Mixture of Gaussians (MoG) is one of the most common background modeling methods, but its accuracy comes at the expense of time, and the effect of noise treatment is general when the background is modeled in RGB color space. To improve MoG, we propose an adaptive MoG background modeling method based on YCbCr. First of all, the modeling color space is converted from RGB into YCbCr. Secondly, adaptive selection strategy is used to determine the number of gaussian components of the MoG. Finally, we order the gaussian components according to the value of sorting key words to determine the background model. The proposed modeling method is applied to moving objects detection experiments, and the experimental results show that the proposed approach is more accurate and less time-consuming in detecting moving objects compared to MoG background modeling.

Key words: background modeling;mixture of Gaussians;YCbCr color space;adaptive selection strategy

黄玉，殷苌茗，周书仁. 基于YCbCr的自适应混合高斯模型背景建模[J]. J4, 2015, 37(01): 152-156.

HUANG Yu,YIN Changming,ZHOU Shuren. An adaptive MoG background modeling based on YCbCr [J]. J4, 2015, 37(01): 152-156.

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