视频图像中的运动目标检测

周同雪; 朱明

doi:10.3788/YJYXS20173201.0040

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视频图像中的运动目标检测

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- 视频图像中的运动目标检测
- Moving target detection of the video images
- 液晶与显示 2017年32卷第1期页码：40-47
- 作者机构：
  
  中国科学院长春光学精密机械与物理研究所, 吉林长春 130033
- 作者简介：
  
  周同雪(1992-),女,吉林敦化人,硕士研究生,2015年毕业于吉林大学,主要从事图像处理方面的研究。E-mail:zhoutongxue1992@163.com
  [ "朱明(1964-),男,江西南昌人,研究员,博士生导师,主要从事视频图像处理,自动目标识别技术及成像目标跟踪等方面的研究" ]
- 基金信息：
- DOI：10.3788/YJYXS20173201.0040
  中图分类号： TN919.8;TP391.4
- 收稿日期：2016-08-24，
  
  录用日期：2016-9-7，
  
  纸质出版日期：2017-01
- 稿件说明：
移动端阅览
周同雪, 朱明. 视频图像中的运动目标检测[J]. 液晶与显示, 2017,32(1):40-47.

Tong-xue ZHOU, Ming ZHU. Moving target detection of the video images[J]. Chinese journal of liquid crystals and displays, 2017, 32(1): 40-47.
周同雪, 朱明. 视频图像中的运动目标检测[J]. 液晶与显示, 2017,32(1):40-47. DOI： 10.3788/YJYXS20173201.0040.

Tong-xue ZHOU, Ming ZHU. Moving target detection of the video images[J]. Chinese journal of liquid crystals and displays, 2017, 32(1): 40-47. DOI： 10.3788/YJYXS20173201.0040.

摘要

运动目标检测，是指从视频图像中将运动变化区域提取出来的检测技术，是图像处理技术的基础。在军事公安、交通管理、视频监控、医学检查等领域应用广泛。为了改进单独采用帧差法或背景减法进行运动目标检测时存在的不足，本文提出一种利用边缘信息的三帧差法与基于混合高斯模型的背景减法相结合的运动目标检测算法。该方法对视频图像中连续的三帧图像两两差分，对3个差分图像取均值，二值化，再经过形态学处理，并对中间帧进行Canny边缘提取，将二者进行“与”运算，即得到运动目标的边缘，用背景减法提取中间帧的前景，二值化，将其和目标的边缘进行“或”运算，经过形态学处理便可得到运动目标。实验结果表明，使用该方法目标检出率提高了9.7%~72.1%，误检率降低了0.090%~2.900%。这种二者相结合的方法相对于单一的检测算法能够有效、可靠地提取出运动目标。

Abstract

Moving target detection technology refers to extracting the change from the video images

and it is widely used in the field of military security

traffic management

video surveillance

medical examination and so on. In order to improve the shortcomings of three-frame-difference method and background subtraction

this paper presents a new moving object detection algorithm based on edge information of the three-frame-difference method combined with the background subtraction. Firstly

the current frame subtracts the previous frame and the next frame separately

the next frame subtracts the previous frame

their results are added together to get a gray-scale image.The result is divided by three. Secondly

the gray-scale image is translated into binary image after being judged by threshold. And then it will be dealt with a series of morphological processing.Thirdly

the Canny edge detection operator is introduced into the middle frame

then the two results "and" operation to get the edge of the moving object.Finally

the current frame image subtracts the background image to get another gray-scale image

in the same way

it is translated into binary image after being judged by threshold. Then the final two results "or" operation. The moving object is got by doing a series of morphological processing. The experimental results show that

target detection rate by using the method increased by 9.7%~72.1%

and the error detection rate is reduced by 0.090%~2.900%. The combination of the two compared with the single detection algorithm can effectively and reliably detect the moving targets.

关键词

Keywords

references

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