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Solar Physics

, Volume 248, Issue 2, pp 277–296 | Cite as

Automated McIntosh-Based Classification of Sunspot Groups Using MDI Images

  • T. Colak
  • R. Qahwaji
Article
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Accepted:

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.

Keywords

Solar Phys Sunspot Group Michelson Doppler Imager Large Spot False Acceptance Rate 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Copyright information

© Springer Science+Business Media B.V. 2007

Authors and Affiliations

  1. 1.Department of Electronic Imaging and Media CommunicationsUniversity of BradfordBradfordUK

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