Proceedings of the 2016 6th International Conference on Mechatronics, Computer and Education Informationization (MCEI 2016)

Improvement Algorithm of Background Updating Based on Kalman Filter

Authors
Jin Wang, Hang Zhou
Corresponding Author
Jin Wang
Available Online December 2016.
DOI
https://doi.org/10.2991/mcei-16.2016.144How to use a DOI?
Keywords
Target detection; Mix-color space; Background updating; Kalman filter
Abstract

In the process of target detection under complex background, the color of target(foreground)is often similar to the color of the background which causes noise during background updating, and the integrity of the target extracted from the image has been affected. In view of this situation, an improved algorithm based on Kalman filter is proposed. The algorithm analyzes the difference of background subtraction results in different channels of multiple color spaces, then the mix-color space is built and the detection results of each channel in the mix-color space are integrated. The background updating algorithm based on Kalman filter has been improved from the update region and the updated background was closer to real background. The experiment results show that under the complex background, the algorithm can remove the background noise effectively with high accuracy and good applicability.In the process of target detection under complex background, the color of target(foreground)is often similar to the color of the background which causes noise during background updating, and the integrity of the target extracted from the image has been affected. In view of this situation, an improved algorithm based on Kalman filter is proposed. The algorithm analyzes the difference of background subtraction results in different channels of multiple color spaces, then the mix-color space is built and the detection results of each channel in the mix-color space are integrated. The background updating algorithm based on Kalman filter has been improved from the update region and the updated background was closer to real background. The experiment results show that under the complex background, the algorithm can remove the background noise effectively with high accuracy and good applicability.In the process of target detection under complex background, the color of target(foreground)is often similar to the color of the background which causes noise during background updating, and the integrity of the target extracted from the image has been affected. In view of this situation, an improved algorithm based on Kalman filter is proposed. The algorithm analyzes the difference of background subtraction results in different channels of multiple color spaces, then the mix-color space is built and the detection results of each channel in the mix-color space are integrated. The background updating algorithm based on Kalman filter has been improved from the update region and the updated background was closer to real background. The experiment results show that under the complex background, the algorithm can remove the background noise effectively with high accuracy and good applicability.In the process of target detection under complex background, the color of target(foreground)is often similar to the color of the background which causes noise during background updating, and the integrity of the target extracted from the image has been affected. In view of this situation, an i

Copyright
© 2017, 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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Volume Title
Proceedings of the 2016 6th International Conference on Mechatronics, Computer and Education Informationization (MCEI 2016)
Series
Advances in Intelligent Systems Research
Publication Date
December 2016
ISBN
978-94-6252-282-4
ISSN
1951-6851
DOI
https://doi.org/10.2991/mcei-16.2016.144How to use a DOI?
Copyright
© 2017, 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/).

Cite this article

TY  - CONF
AU  - Jin Wang
AU  - Hang Zhou
PY  - 2016/12
DA  - 2016/12
TI  - Improvement Algorithm of Background Updating Based on Kalman Filter
BT  - Proceedings of the 2016 6th International Conference on Mechatronics, Computer and Education Informationization (MCEI 2016)
PB  - Atlantis Press
SP  - 694
EP  - 699
SN  - 1951-6851
UR  - https://doi.org/10.2991/mcei-16.2016.144
DO  - https://doi.org/10.2991/mcei-16.2016.144
ID  - Wang2016/12
ER  -