Paper
1 August 2023 Spatial target detection method based on frame difference and target characteristics
Junyou Qin, Zhihua Shen, Han Wang, Xiaohu Zhang, Xia Yang
Author Affiliations +
Proceedings Volume 12754, Third International Conference on Computer Vision and Pattern Analysis (ICCPA 2023); 127541K (2023) https://doi.org/10.1117/12.2684511
Event: 2023 3rd International Conference on Computer Vision and Pattern Analysis (ICCPA 2023), 2023, Hangzhou, China
Abstract
In space observation, star maps contain a large number of stars and noise, whose characteristics are similar to those of the targets that need to be detected. Traditional methods struggle to ensure both high efficiency and accuracy simultaneously. This paper proposes a space target detection method based on frame difference and target characteristics. Firstly, the star map is registered, then the background is suppressed using frame difference method and noise interference is reduced by Gaussian blurring. Finally, a multi-scale local target characteristic algorithm is used to calculate three feature parameters of suspected regions to further screen the targets. Experimental results show that the proposed algorithm significantly reduces false alarms while ensuring correct detection rates, and its speed is significantly improved. The algorithm fully utilizes the advantages of the frame difference method and the multi-scale local target characteristic algorithm, thus improving the detection efficiency and accuracy.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Junyou Qin, Zhihua Shen, Han Wang, Xiaohu Zhang, and Xia Yang "Spatial target detection method based on frame difference and target characteristics", Proc. SPIE 12754, Third International Conference on Computer Vision and Pattern Analysis (ICCPA 2023), 127541K (1 August 2023); https://doi.org/10.1117/12.2684511
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KEYWORDS
Target detection

Detection and tracking algorithms

Image filtering

Gaussian filters

Point spread functions

Object detection

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