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Abstract
In order to solve the practical application problem of the automatic target-scoring system based on computer vision under dynamic interference conditions such as flying catkins, this paper improves the traditional detection and removal methods of frame difference method and mean value method and proposes an effective flying catkins detection and removal algorithm based on time domain and brightness characteristics by fully studying the characteristics of flying catkins in target video and existing rain and snow removal algorithm. Experiments show that this method can effectively solve the problem of missed detection caused by the multiple moving states of flying catkins and realize the rapid flying catkins removal of the target video with good robustness and timeliness.
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Authors and Affiliations
Naval Aviation University, Yaitai, China
Hualin Liu, Haipeng Wang, Limin Zhang & Xueteng Li
- Hualin Liu
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- Haipeng Wang
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- Limin Zhang
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- Xueteng Li
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Corresponding author
Correspondence toHualin Liu.
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Editors and Affiliations
Department of Electrical Engineering, University of Texas at Arlington, Arlington, TX, USA
Qilian Liang
College of Electronic and Communication Engineering, Tianjin Normal University, Tianjin, China
Wei Wang
School of Information and Communication Engineering, Dalian University of Technology, Dalian, Liaoning, China
Xin Liu
School of Information Science and Technology, Dalian Maritime University, Dalian, Liaoning, China
Zhenyu Na
School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin, China
Min Jia
College of Physical and Electronic Information, Tianjin Normal University, Tianjin, China
Baoju Zhang
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Liu, H., Wang, H., Zhang, L., Li, X. (2020). Research on Flying Catkins Detection and Removal in Target Video. In: Liang, Q., Wang, W., Liu, X., Na, Z., Jia, M., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2019. Lecture Notes in Electrical Engineering, vol 571. Springer, Singapore. https://doi.org/10.1007/978-981-13-9409-6_99
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