Solar Physics

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

Automated McIntosh-Based Classification of Sunspot Groups Using MDI Images

  • T. ColakEmail author
  • R. Qahwaji


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.


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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  1. Curto, J.J., Blanca, M., Solé, J.G.: 2003, Solar Image Recognition Workshop.
  2. Fukunaga, K.: 1990, Introduction to Statistical Pattern Recognition, Academic Press, New York, 220. zbMATHGoogle Scholar
  3. Hathaway, D., Wilson, R.M., Reichmann, E.J.: 1994, Solar Phys. 151, 177. CrossRefADSGoogle Scholar
  4. Hong, L., Jain, A.: 1997, IEEE Trans. Pattern Anal. Mach. Intel. 20, 1295. CrossRefGoogle Scholar
  5. Künzel, H.: 1960, Astron. Nachr. 285, 271. CrossRefADSGoogle Scholar
  6. Kim, J., Owat, A., Poole, P., Kasabov, N.: 2000, Chemometr. Intel. Lab. Syst. 51, 201. CrossRefGoogle Scholar
  7. McIntosh, P.S.: 1990, Solar. Phys. 125, 251. CrossRefADSGoogle Scholar
  8. Meeus, J.: 1998, Astronomical Algorithms, 2nd edn. Willmann-Bell, Richmond. Google Scholar
  9. Nguyen, S.H., Nguyen, T.T., Nguyen, H.S., 2005, Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing 3642, Springer, Heidelberg, 263. Google Scholar
  10. Phillips, K.J.H.: 1992, Guide to the Sun, Cambridge University Press, Cambridge. Google Scholar
  11. Qahwaji, R., Colak, T.: 2006a, Int. J. Imaging Syst. Technol. 15, 199. CrossRefGoogle Scholar
  12. Qahwaji, R., Colak, T.: 2006b, Int. J. Comput. Appl. 13, 9. Google Scholar
  13. Qahwaji, R., Colak, T.: 2007, Solar Phys. 241, 195. CrossRefADSGoogle Scholar
  14. Sakurai, K.: 1970, Planet Space Sci. 18, 33. CrossRefADSGoogle Scholar
  15. Scherrer, P.H., Bogart, R.S., Bush, R.I., Hoeksema, J.T., Kosovichev, A.G., Schou, J., Rosenberg, W., Springer, L., Tarbell, T.D., Title, A., Wolfson, C.J., Zayer, I., Akin, D., Carvalho, B., Chevalier, R., Duncan, D., Edwards, C., Katz, N., Levay, M., Lindgren, R., Mathur, D., Morrison, S., Pope, T., Rehse, R., Torgerson, D.: 1995, Solar Phys. 162, 129. CrossRefADSGoogle Scholar
  16. Severny, A.B.: 1965, In: Lust, R. (ed.) Stellar and Solar Magnetic Fields, IAU Symp. No. 22, North-Holland, Amsterdam, 358. Google Scholar
  17. Warwick, C.S.: 1966, Astrophys. J. 145, 215. CrossRefADSGoogle Scholar
  18. Zharkov, S., Zharkova, V., Ipson, S., Benkhalil, A.: 2004, In: Negoita, M.G., Howlett, R.J., Jain, L.C. (eds.) Knowledge-Based Intelligent Information and Engineering Systems, Pt 3, Proceedings, Lecture Notes in Computer Science 3215, 446. Google Scholar

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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