• DocumentCode
    3450089
  • Title

    A Survey of Solar Filament Detection Methods

  • Author

    Pingting Peng ; Kaifan Ji ; Feng Wang

  • Author_Institution
    Yunnan Comput. Technol. Applic. Key Lab., Kunming Univ. of Sci. & Technol., Kunming, China
  • fYear
    2013
  • fDate
    1-3 Nov. 2013
  • Firstpage
    320
  • Lastpage
    323
  • Abstract
    Solar filament is one of the main features of the sun. As a forecasting aid for geomagnetic storms, also, it is the subject of space weather study. Many methods have been proposed to detect the solar filaments, but most of them are manual feature recognition techniques. In this paper, three kinds of automated detection methods for filaments are presented. They are respectively automated region growing procedure, a threshold and region growing combined method and Artificial Neural Network technique (ANN). The experimental results are presented and the advantages and disadvantages of these three methods are compared. Automated region growing method can represent more details of filaments, however, it is time-consuming and strongly dependents on the background cleaning procedures. Threshold and region growing combined method can effectively improve the speed of image processing, but it can´t detect the filaments near the solar limb. ANN can resolve these drawbacks which exist in automated region growing procedure and it has the ability of recognizing multiplicative filaments.
  • Keywords
    astronomical image processing; astronomical techniques; feature extraction; magnetic storms; neural nets; solar prominences; artificial neural network technique; automated detection methods; automated region growing method; background cleaning procedures; forecasting aid; geomagnetic storms; image processing; manual feature recognition techniques; multiplicative filaments; solar filament detection methods; solar limb; space weather; threshold and region growing combined method; Artificial neural networks; Feature extraction; Image segmentation; Neurons; Physics; Sun; Vectors; automated detection; feature recognition; solar filament;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Networks and Intelligent Systems (ICINIS), 2013 6th International Conference on
  • Conference_Location
    Shenyang
  • Print_ISBN
    978-1-4799-2808-8
  • Type

    conf

  • DOI
    10.1109/ICINIS.2013.89
  • Filename
    6754738