Labrosse, N., Dalla, S. and Marshall, S. (2010) Automatic Detection of Limb Prominences in 304 Å EUV Images. Solar Physics, 262 (2). pp. 449-460. ISSN 0038-0938
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Official URL: http://dx.doi.org/10.1007/s11207-009-9492-9
A new algorithm for automatic detection of prominences on the solar limb in 304 Å 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 the 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.
|Uncontrolled Keywords (separate with ;):||Corona, structures ; Prominences, quiescent ; Prominences, active|
|Subjects:||Physical sciences > Physics|
|Schools:||College of Science and Technology > School of Physical Sciences and Computing > Jeremiah Horrocks Institute|
|Deposited By:||Helen Cooper|
|Deposited On:||20 Mar 2012 13:39|
|Last Modified:||17 May 2016 12:29|
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