Can we determine the filament chirality by the filament footpoint location or the barb-bearing?

Qi Hao, Yang Guo, Cheng Fang, Peng Fei Chen, Wenda Cao

Research output: Contribution to journalArticlepeer-review

11 Scopus citations


We attempt to propose a method for automatically detecting the solar filament chirality and barb bearing. We first introduce the concept of an unweighted undirected graph and adopt the Dijkstra shortest path algorithm to recognize the filament spine. Then, we use the polarity inversion line (PIL) shift method for measuring the polarities on both sides of the filament, and employ the connected components labeling method to identify the barbs and calculate the angle between each barb and the spine to determine the bearing of the barbs, i.e., left or right. We test the automatic detection method with Hα filtergrams from the Big Bear Solar Observatory (BBSO) Hα archive and magnetograms observed with the Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamics Observatory (SDO). Four filaments are automatically detected and illustrated to show the results. The barbs in different parts of a filament may have opposite bearings. The filaments in the southern hemisphere (northern hemisphere) mainly have left-bearing (right-bearing) barbs and positive (negative) magnetic helicity, respectively. The tested results demonstrate that our method is efficient and effective in detecting the bearing of filament barbs. It is demonstrated that the conventionally believed one-to-one correspondence between filament chirality and barb bearing is not valid. The correct detection of the filament axis chirality should be done by combining both imaging morphology and magnetic field observations.

Original languageEnglish (US)
Article number001
JournalResearch in Astronomy and Astrophysics
Issue number1
StatePublished - Jan 2016

All Science Journal Classification (ASJC) codes

  • Astronomy and Astrophysics
  • Space and Planetary Science


  • Sun: chromosphere
  • Sun: filaments, prominences
  • Sun: magnetic fields
  • techniques: image processing


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