Institutional Repository of Optical Astronomy Research Laboratory
Rapid automatic multiple moving objects detection method based on feature extraction from images with non-sidereal tracking | |
Wang, Lei1,2; Zhang, Xiaoming1,2; Bai, Chunhai3![]() ![]() | |
2024-09-18 | |
Source Publication | MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
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ISSN | 0035-8711 |
Volume | 534Issue:1Pages:385-399 |
Contribution Rank | 3 |
Abstract | Optically observing and monitoring moving objects, both natural and artificial, is important to human space security. Non-sidereal tracking can improve the system's limiting magnitude for moving objects, which benefits the surveillance. However, images with non-sidereal tracking include complex background, as well as objects with different brightness and moving mode, posing a significant challenge for accurate multi-object detection in such images, especially in wide field-of-view telescope images. To achieve a higher detection precision in a higher speed, we proposed a novel object detection method, which combines the source feature extraction and the neural network. First, our method extracts object features from optical images such as centroid, shape, and flux. Then, it conducts a naive labelling based on those features to distinguish moving objects from stars. After balancing the labelled data, we employ it to train a neural network aimed at creating a classification model for point-like and streak-like objects. Ultimately, based on the neural network model's classification outcomes, moving objects whose motion modes consistent with the tracked objects are detected via track association, while objects with different motion modes are detected using morphological statistics. The validation, based on the space objects images captured in target tracking mode with the 1-m telescope at Nanshan, Xinjiang Astronomical Observatory, demonstrates that our method achieves 94.72 per cent detection accuracy with merely 5.02 per cent false alarm rate, and a processing time of 0.66 s per frame. Consequently, our method can rapidly and accurately detect objects with different motion modes from wide-field images with non-sidereal tracking. |
Keyword | methods: data analysis techniques: image processing planets and satellites: detection |
DOI | 10.1093/mnras/stae2073 |
Indexed By | SCI |
Language | 英语 |
WOS Keyword | SPACE-DEBRIS ; WIDE-FIELD ; ALGORITHMS ; ASTROMETRY ; PHOTOMETRY ; TARGETS ; FAINT |
Funding Project | National Science and Technology Major Project[2022ZD0117401] ; National Natural Science Foundation of China[12273063] |
WOS Research Area | Astronomy & Astrophysics |
WOS Subject | Astronomy & Astrophysics |
WOS ID | WOS:001315413300006 |
Publisher | OXFORD UNIV PRESS |
Funding Organization | National Science and Technology Major Project ; National Natural Science Foundation of China |
Citation statistics | |
Document Type | 期刊论文 |
Identifier | http://ir.xao.ac.cn/handle/45760611-7/6994 |
Collection | 光学天文与技术应用研究室_光学天文技术研究团组 科研仪器设备产出_利用南山1米大视场望远镜(NOWT)观测数据的文章 |
Corresponding Author | Wang, Lei; Zhang, Xiaoming; Jiang, Xiaojun |
Affiliation | 1.Chinese Acad Sci, CAS Key Lab Opt Astron, Natl Astron Observ, Beijing 100101, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 3.Chinese Acad Sci, Xinjiang Astron Observ, Urumqi 830011, Peoples R China 4.Chinese Acad Sci, Changchun Observ, Natl Astron Observ, Changchun 130117, Peoples R China |
Recommended Citation GB/T 7714 | Wang, Lei,Zhang, Xiaoming,Bai, Chunhai,et al. Rapid automatic multiple moving objects detection method based on feature extraction from images with non-sidereal tracking[J]. MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY,2024,534(1):385-399. |
APA | Wang, Lei.,Zhang, Xiaoming.,Bai, Chunhai.,Xie, Haiwen.,Li, Juan.,...&Jiang, Xiaojun.(2024).Rapid automatic multiple moving objects detection method based on feature extraction from images with non-sidereal tracking.MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY,534(1),385-399. |
MLA | Wang, Lei,et al."Rapid automatic multiple moving objects detection method based on feature extraction from images with non-sidereal tracking".MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY 534.1(2024):385-399. |
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Wang-2024-Rapid auto(2144KB) | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | View Application Full Text |
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