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Automated McIntosh-Based Classification of Sunspot Groups Using MDI Images
Colak, Tufan
Colak, Tufan
Publication Date
2007-12-16
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© 2007 Springer. Reproduced in accordance with the publisher's self-archiving policy. Original publication is available at https://www.springerlink.com
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openAccess
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colak_et_al_2007
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Abstract
This paper presents a hybrid system for automatic detection and McIntosh-based classification of sunspot groups on SOHO/MDI white-light images using active-region data extracted from SOHO/MDI magnetogram images. After sunspots are detected from MDI white-light images they are grouped/clustered using MDI magnetogram images. By integrating image-processing and neural network techniques, detected sunspot regions are classified automatically according to the McIntosh classification system. Our results show that the automated grouping and classification of sunspots is possible with a high success rate when compared to the existing manually created catalogues. In addition, our system can detect and classify sunspot groups in their early stages, which are usually missed by human observers.
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Accepted manuscript
Citation
Colak T and Qahwaji R (2007) Automated McIntosh-Based Classification of Sunspot Groups Using MDI Images. Solar Physics. 248(2): 277-296.
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Article