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Technique for Automated Recognition of Sunspots on Full-Disk Solar Images

Abstract

A new robust technique is presented for automated identification of sunspots on full-disk white-light (WL) solar images obtained from SOHO/MDI instrument and Ca II K1 line images from the Meudon Observatory. Edge-detection methods are applied to find sunspot candidates followed by local thresholding using statistical properties of the region around sunspots. Possible initial oversegmentation of images is remedied with a median filter. The features are smoothed by using morphological closing operations and filled by applying watershed, followed by dilation operator to define regions of interest containing sunspots. A number of physical and geometrical parameters of detected sunspot features are extracted and stored in a relational database along with umbra-penumbra information in the form of pixel run-length data within a bounding rectangle. The detection results reveal very good agreement with the manual synoptic maps and a very high correlation with those produced manually by NOAA Observatory, USA.

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Correspondence to S. Zharkov.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License ( https://creativecommons.org/licenses/by/2.0 ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Zharkov, S., Zharkova, V., Ipson, S. et al. Technique for Automated Recognition of Sunspots on Full-Disk Solar Images. EURASIP J. Adv. Signal Process. 2005, 318462 (2005). https://doi.org/10.1155/ASP.2005.2573

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Keywords and phrases

  • digital solar image
  • sunspots
  • local threshold
  • edge-detection
  • morphological operators
  • sunspot area time series