Solar Physics

, 272:101 | Cite as

Automatic Solar Filament Segmentation and Characterization



This paper presents a generic method to automatically segment and characterize solar filaments from various Hα full-disk solar images, obtained by different solar observatories, with different dynamic ranges and statistical properties. First, a cascading Hough circle detector is designed to find the center location and radius of the solar disks. Second, polynomial surface fitting is adopted to correct unbalanced luminance. Third, an adaptive thresholding method is put forward to segment solar filaments. Finally, for each piece of a solar filament, its centroid location, area, and length are characterized, in which morphological thinning and graph theory are used for identifying the main skeletons of filaments. To test the performance of the proposed methods, a dataset composed of 125 Hα images is considered. These images were obtained by four solar observatories from January 2000 to May 2010, one image per month. Experimental results show that the accuracy rate is above 95% as measured by filament number and above 99% as measured by filament area, indicating that only a few tiny filaments are not detected.


Coronal Mass Ejection Solar Phys Center Location Solar Disk Edge Point 
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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Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • Y. Yuan
    • 1
  • F. Y. Shih
    • 1
  • J. Jing
    • 2
  • H. Wang
    • 2
  • J. Chae
    • 3
  1. 1.Computer Vision LabNew Jersey Institute of TechnologyNewarkUSA
  2. 2.Space Weather Research LabNew Jersey Institute of TechnologyNewarkUSA
  3. 3.Department of Physics and AstronomySeoul National UniversitySeoulRepublic of Korea

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