Abstract
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.
Article PDF
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.Avoid common mistakes on your manuscript.
References
Aboudarham, J., Scholl, I.F., Fuller, N., Fouesneau, M., Gonon, F., Maire, A., Leroy, Y.: 2008, Automated detection and tracking of filaments for a solar feature database. Astrophys. J. 26, 248.
Aizerman, M., Braverman, E., Rozonoer, L.: 1964, Theoretical foundations of the potential function method in pattern recognition learning. Autom. Remote Control 25, 837.
Anzer, U., Heinzel, P.: 2005, On the nature of dark extreme ultraviolet structures seen by SOHO/EIT and TRACE. Astrophys. J. 622, 721. doi:10.1086/427817.
Aschwanden, M.J., Wuelser, J.P., Nitta, N.V., Lemen, J.R.: 2009, Solar flare and CME observations with STEREO/EUVI. Solar Phys. 256, 40. doi:10.1007/s11207-009-9347-4.
Auchère, F., Artzner, G.E.: 2004, EIT observations of the 15 November 1999 Mercury transit. Solar Phys. 219, 230. doi:10.1023/B:SOLA.0000022945.53373.17.
Bernasconi, P.N., Rust, D.M., Hakim, D.: 2005, Advanced automated solar filament detection and characterization code: Description, performance, and results. Solar Phys. 228, 117. doi:10.1007/s11207-005-2766-y.
Chang, C.C., Lin, C.J.: 2001, LIBSVM: A Library for Support Vector Machines. Software available at http://www.csie.ntu.edu.tw/~cjlin/libsvm.
Cortes, C., Vapnik, V.: 1995, Support-vector networks. Mach. Learn. 20(3), 297. doi:10.1023/A:1022627411411.
Cristianini, N., Shawe-Taylor, J.: 2000, An Introduction to Support Vector Machines and Other Kernel-Based Learning Methods, Cambridge University Press, New York. ISBN 0-521-78019-5.
Foullon, C., Verwichte, E.: 2006, Automated detection of EUV prominences. Solar Phys. 234, 150. doi:10.1007/s11207-006-0054-0.
Fu, G., Shih, F.Y., Wang, H.: 2007, Automated detection of prominence eruption using consecutive solar images. IEEE Trans. Circuits Syst. Video Technol. 17, 85.
Fuller, N., Aboudarham, J., Bentley, R.D.: 2005, Filament recognition and image cleaning on Meudon Hα spectroheliograms. Solar Phys. 227, 73. doi:10.1007/s11207-005-8364-1.
Gilbert, H.R., Holzer, T.E., Burkepile, J.T., Hundhausen, A.J.: 2000, Active and eruptive prominences and their relationship to coronal mass ejections. Astrophys. J. 537, 515.
Gopalswamy, N., Yashiro, S., Michalek, G., Stenborg, G., Vourlidas, A., Freeland, S., Howard, R.: 2009, The SOHO/LASCO CME catalog. Earth Moon Planets 104, 313. doi:10.1007/s11038-008-9282-7.
Heinzel, P., Schmieder, B., Fárník, F., Schwartz, P., Labrosse, N., Kotrč, P., Anzer, U., Molodij, G., Berlicki, A., DeLuca, E.E., Golub, L., Watanabe, T., Berger, T.: 2008, Hinode, TRACE, SOHO, and ground-based observations of a quiescent prominence. Astrophys. J. 686, 1396. doi:10.1086/591018.
Mackay, D.H., Gaizauskas, V., Yeates, A.R.: 2008, Where do solar filaments form? Consequences for theoretical models. Solar Phys. 248, 65. doi:10.1007/s11207-008-9127-6.
Patsourakos, S., Vial, J.C.: 2002, Soho contribution to prominence science. Solar Phys. 208, 281.
Robbrecht, E., Berghmans, D., Van der Linden, R.A.M.: 2009, Automated LASCO CME catalog for solar cycle 23: Are CMEs scale invariant? Astrophys. J. 691, 1234. doi:10.1088/0004-637X/691/2/1222.
Scholl, I.F., Habbal, S.R.: 2008, Automatic detection and classification of coronal holes and filaments based on EUV and magnetogram observations of the solar disk. Solar Phys. 248, 439. doi:10.1007/s11207-007-9075-6.
Shimojo, M., Yokoyama, T., Asai, A., Nakajima, H., Shibasaki, K.: 2006, One solar-cycle observations of prominence activities using the Nobeyama radioheliograph 1992 – 2004. Publ. Astron. Soc. Japan 58, 92.
Zharkova, V.V., Aboudarham, J., Zharkov, S., Ipson, S.S., Benkhalil, A.K., Fuller, N.: 2005, Solar feature catalogues in Egso. Solar Phys. 228, 375. doi:10.1007/s11207-005-5623-0.
Author information
Authors and Affiliations
Corresponding author
Additional information
Solar Image Processing and Analysis
Guest Editors: J. Ireland and C.A. Young
Rights and permissions
About this article
Cite this article
Labrosse, N., Dalla, S. & Marshall, S. Automatic Detection of Limb Prominences in 304 Å EUV Images. Sol Phys 262, 449–460 (2010). https://doi.org/10.1007/s11207-009-9492-9
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11207-009-9492-9