Automated McIntosh-Based Classification of Sunspot Groups Using MDI Images
- 294 Downloads
- 54 Citations
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 RatePreview
Unable to display preview. Download preview PDF.
References
- Curto, J.J., Blanca, M., Solé, J.G.: 2003, Solar Image Recognition Workshop. http://sol.oma.be/SIRW/SIRWpres/Curto.PDF.
- Fukunaga, K.: 1990, Introduction to Statistical Pattern Recognition, Academic Press, New York, 220. zbMATHGoogle Scholar
- Hathaway, D., Wilson, R.M., Reichmann, E.J.: 1994, Solar Phys. 151, 177. CrossRefADSGoogle Scholar
- Hong, L., Jain, A.: 1997, IEEE Trans. Pattern Anal. Mach. Intel. 20, 1295. CrossRefGoogle Scholar
- Künzel, H.: 1960, Astron. Nachr. 285, 271. CrossRefADSGoogle Scholar
- Kim, J., Owat, A., Poole, P., Kasabov, N.: 2000, Chemometr. Intel. Lab. Syst. 51, 201. CrossRefGoogle Scholar
- McIntosh, P.S.: 1990, Solar. Phys. 125, 251. CrossRefADSGoogle Scholar
- Meeus, J.: 1998, Astronomical Algorithms, 2nd edn. Willmann-Bell, Richmond. Google Scholar
- 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
- Phillips, K.J.H.: 1992, Guide to the Sun, Cambridge University Press, Cambridge. Google Scholar
- Qahwaji, R., Colak, T.: 2006a, Int. J. Imaging Syst. Technol. 15, 199. CrossRefGoogle Scholar
- Qahwaji, R., Colak, T.: 2006b, Int. J. Comput. Appl. 13, 9. Google Scholar
- Qahwaji, R., Colak, T.: 2007, Solar Phys. 241, 195. CrossRefADSGoogle Scholar
- Sakurai, K.: 1970, Planet Space Sci. 18, 33. CrossRefADSGoogle Scholar
- 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
- Severny, A.B.: 1965, In: Lust, R. (ed.) Stellar and Solar Magnetic Fields, IAU Symp. No. 22, North-Holland, Amsterdam, 358. Google Scholar
- Warwick, C.S.: 1966, Astrophys. J. 145, 215. CrossRefADSGoogle Scholar
- 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