[1]于晓明,李思颖,史胜楠.混合高斯融合三帧差的运动目标检测改进算法[J].红外技术,2019,41(3):256-261.[doi:10.11846/j.issn.1001_8891.201903010]
 YU Xiaoming,LI Siying,SHI Shengnan.An Improved Algorithm for Moving Target Detection Using a Gaussian Mixture with Three-frame Difference[J].Infrared Technology,2019,41(3):256-261.[doi:10.11846/j.issn.1001_8891.201903010]
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混合高斯融合三帧差的运动目标检测改进算法
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《红外技术》[ISSN:1001-8891/CN:CN 53-1053/TN]

卷:
41卷
期数:
2019年第3期
页码:
256-261
栏目:
出版日期:
2019-03-20

文章信息/Info

Title:
An Improved Algorithm for Moving Target Detection Using a Gaussian Mixture with Three-frame Difference
文章编号:
1001-8891(2019)03-0256-06
作者:
于晓明李思颖史胜楠
陕西科技大学 电气与信息工程学院
Author(s):
YU XiaomingLI SiyingSHI Shengnan
School of Electrical and Information Engineering, Shaanxi University of Science and Technology
关键词:
混合高斯模型三帧差法目标检算法测边缘检测颜色空间
Keywords:
Gaussian mixture modelthree frame difference methodtarget detection algorithmedge detectioncolor space
分类号:
TP391
DOI:
10.11846/j.issn.1001_8891.201903010
文献标志码:
A
摘要:
针对混合高斯模型(Gaussian Mixture Model,GMM)无法检测到完整的运动目标,三帧差法检测目标时对物体速度的敏感,检测到的物体会出现空洞等缺点,提出了一种混合高斯融合三帧差法的运动目标检测改进算法。首先,在运动目标提取过程中,改进的三帧差法采用动态分割阈值和边缘检测技术,解决光线突变和边缘不连续问题;然后引入新的高斯分布自适应选择策略,以减少处理时间,提高检测准确性;最后,利用改进HSV(Hue-Saturation-Value)颜色空间来消除阴影区域,得到一个完整的运动目标。数据实验表明,该算法在不同场景具有较好的检测能力。
Abstract:
Gaussian mixture model,three frame difference method,target detection algorithm,edge detection,color space

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2018-05-22;修订日期:2018-07-16.
作者简介:李思颖(1993-),女,硕士研究生,主要从事运动目标检测与跟踪方面的研究。E-mail:1032570969@qq.com。
通信作者:于晓明(1965-),女,博士,副教授,主要从事图像处理、计算机视觉方面的研究。
基金项目:陕西省科技厅项目(2014KRM80);咸阳市科技局项目(2013K15-07)。

更新日期/Last Update: 2019-03-19