Detection of Moving Objects Based on the Gaussian Mixture Model and the Canny Operator

CHEN  Shi-Wen; Cai-Nian; Xiao-Ming-Ming

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Detection of Moving Objects Based on the Gaussian Mixture Model and the Canny Operator

更新时间：2026-05-27

- Detection of Moving Objects Based on the Gaussian Mixture Model and the Canny Operator
- Vol. 28, Issue 3, Pages: 87-91(2011)
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- Online First：06 October 2010，
  
  Published：2011
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陈世文, 蔡念, 肖明明. 基于高斯混合模型和canny算法的运动目标检测[J]. 广东工业大学学报, 2011, 28(3): 87-91.

CHEN Shi-Wen, Cai-Nian, Xiao-Ming-Ming. Detection of Moving Objects Based on the Gaussian Mixture Model and the Canny Operator[J]. 2011, 28(3): 87-91.
陈世文, 蔡念, 肖明明. 基于高斯混合模型和canny算法的运动目标检测[J]. 广东工业大学学报, 2011, 28(3): 87-91. DOI：

CHEN Shi-Wen, Cai-Nian, Xiao-Ming-Ming. Detection of Moving Objects Based on the Gaussian Mixture Model and the Canny Operator[J]. 2011, 28(3): 87-91. DOI：

摘要

提出一种基于高斯混合模型和canny算法的运动目标检测算法.利用高斯混合模型计算像素之间的颜色信息，同时利用高斯混合模型更新背景信息；用canny算子提取图像的边缘信息；将颜色信息和区域结构信息线性融合起来，较好地解决了边缘信息明显的运动目标检测.实验中采用改进的加权高斯模型及传统的canny算法相结合.结果表明，本文方法比经典高斯混合模型方法具有较高的分割精度，鲁棒性较好.

Abstract

A method of detecting moving objects is proposed by combining the Gaussian mixture model with the canny operator. First

the Gaussian mixture model was employed to extract color information and to update the background information. Second

the canny operator was employed to extract edge information. Last

color information and part of area information were integrated for segmentation

which improved the ability to detect moving objects where edge information was distinct. An improved Gaussian mixture model and a traditional canny algorithm were employed in the experiment. Experimental results indicate that the proposed method is superior to the traditional Gaussian mixture model.

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references

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