Automatic Detection of Limb Prominences in 304 A EUV Images

Details Automatic Detection of Limb Prominences in 304 A EUV Images Automatic Detection of Limb Prominences in 304 A EUV Images

2009-12-06

arxiv.org/abs/0912.1099v1

Solar Phys.262:449-460,2010

Astronomy and Astrophysics

Astrophysics

Solar and Stellar Astrophysics

13 pages, 6 figures (4 coloured)

Scientific paper

10.1007/s11207-009-9492-9

A new algorithm for automatic detection of prominences on the solar limb in 304 A EUV images is presented, and results of its application to SOHO/EIT data discussed. The detection is based on the method of moments combined with a classifier analysis aimed at discriminating between limb prominences, active regions, and the quiet corona. This classifier analysis is based on a Support Vector Machine (SVM). Using a set of 12 moments of the radial intensity profiles, the algorithm performs well in discriminating between the above three categories of limb structures, with a misclassification rate of 7%. Pixels detected as belonging to a prominence are then used as starting point to reconstruct the whole prominence by morphological image processing techniques. It is planned that a catalogue of limb prominences identified in SOHO and STEREO data using this method will be made publicly available to the scientific community.

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