An Automatic Detection for Solar Active Regions Based on Scale-Invariant Feature Transform and Clustering by Fast Search and Find of Density Peaks Article Swipe
Bo Jiang
,
Lei Liu
,
Zheng Sheng
,
Yang Shan-shan
,
Shuguang Zeng
,
Huang Yao
,
Xiaoyu Luo
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1016/j.chinastron.2022.09.007
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1016/j.chinastron.2022.09.007
The solar active regions are the regions where various active phenomena occur in the solar atmosphere. Accurate detection and identification of the solar active regions are of great scientific significance to understand the formation mechanism of the solar magnetic field. In this paper, we propose an automatic detection and recognition technology for solar active regions based on the advantages of Scale Invariant Feature Transform (SIFT) and Clustering by Fast Search and Find of Density Peaks (DPC). Firstly, enhance the contrast of longitudinal magnetic image of Helioseismic and Magnetic Imager (HMI) of Solar Dynamics Observatory (SDO). Then extract the feature points by SIFT. Finally, cluster the feature points by fast search and find of density peaks so as to automatically detect and identify the solar active regions. The results show that the combination of SIFT and DPC can accurately detect the solar active region without human-computer interaction.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.chinastron.2022.09.007
- OA Status
- hybrid
- Cited By
- 6
- References
- 5
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4312292695
All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4312292695Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1016/j.chinastron.2022.09.007Digital Object Identifier
- Title
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An Automatic Detection for Solar Active Regions Based on Scale-Invariant Feature Transform and Clustering by Fast Search and Find of Density PeaksWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2022Year of publication
- Publication date
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2022-07-01Full publication date if available
- Authors
-
Bo Jiang, Lei Liu, Zheng Sheng, Yang Shan-shan, Shuguang Zeng, Huang Yao, Xiaoyu LuoList of authors in order
- Landing page
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https://doi.org/10.1016/j.chinastron.2022.09.007Publisher landing page
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YesWhether a free full text is available
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hybridOpen access status per OpenAlex
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https://doi.org/10.1016/j.chinastron.2022.09.007Direct OA link when available
- Concepts
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Physics, Scale-invariant feature transform, Cluster analysis, Solar observatory, Feature (linguistics), Astrophysics, Pattern recognition (psychology), Artificial intelligence, Magnetic field, Feature extraction, Computer science, Linguistics, Quantum mechanics, PhilosophyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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6Total citation count in OpenAlex
- Citations by year (recent)
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2025: 2, 2024: 3, 2023: 1Per-year citation counts (last 5 years)
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5Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| publication_year | 2022 |
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