Automatic detection of active region on EUV solar images using fuzzy clustering

  • Authors:

  • M. Carmen Aranda;Carlos Caballero

  • Affiliations:

  • Department of Languages and Computer Science, Engineerings School, University of Malaga, Màlaga, España, Spain;Department of Languages and Computer Science, Engineerings School, University of Malaga, Màlaga, España, Spain

  • Venue:
  • IPMU'10 Proceedings of the Computational intelligence for knowledge-based systems design, and 13th international conference on Information processing and management of uncertainty
  • Year:
  • 2010

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Abstract

The technique presented in this paper is based on fuzzy clustering in order to achieve robust automatic detection of active regions in solar images. The first part of the detection process is based on seed selection and region growing. After that, the regions obtained are grouped into real active regions using a fuzzy clustering algorithm. The procedure developed has been tested on 400 full-disk solar images (corresponding to 4 days) taken from the satellite SOHO. The results are compared with those manually generated for the same days and a very good correspondence is found, showing the robustness of the method described.