A Moving Object Extraction Algorithm Based on Hybrid Background Subtraction and Pixel Mean Technique

DOI

10.2991/amcce-18.2018.62How to use a DOI?

Keywords

Pixel mean technique; Morphological recognition technology; Background modeling; Background subtraction method

Abstract

In this paper, a moving object extraction algorithm based on hybrid background subtraction and pixel mean is proposed to solve the problem that the existing object extraction algorithm can not adapt to the moving environment. The algorithm operation process includes target location identification, domain pixel mean value processing, image difference operation, background noise processing. Firstly, the processing frame is intercepted from the motion video and the thermal technology is used to recognize position of the moving target and get the preprocessing region. Then morphological recognition technique is used to recognize the target and establish the orthogonal rectangle enclosing the moving target. By means of domain pixel averaging, the background of the area in the orthogonal rectangle is modeled to obtain the background frame. Finally, the differential operation of processing frame and background frame is carried out, and then the target extraction results are obtained after the gray processing and binary processing. The experimental results show that this algorithm can effectively extract moving targets when it works in the motion environment, successfully merge the background subtraction method and the pixel mean value technique, and update the performance of the background subtraction method in the motion environment.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Junxiang Chen
AU  - Xinghua Lu
AU  - Mingming Ye
AU  - Zhong Ming
AU  - Fang Zhou
AU  - Yulin Luo
PY  - 2018/05
DA  - 2018/05
TI  - A Moving Object Extraction Algorithm Based on Hybrid Background Subtraction and Pixel Mean Technique
BT  - Proceedings of the 2018 3rd International Conference on Automation, Mechanical Control and Computational Engineering (AMCCE 2018)
PB  - Atlantis Press
SP  - 360
EP  - 368
SN  - 2352-5401
UR  - https://doi.org/10.2991/amcce-18.2018.62
DO  - 10.2991/amcce-18.2018.62
ID  - Chen2018/05
ER  -