Detection and tracking of coronal mass ejections based on supervised segmentation and level set

Coronal mass ejection (CME) events refer to the appearance of a new, discrete, white-light feature (with outward velocity) in a coronagraph. The huge amount of data provided by the pertinent instruments onboard the Solar and Heliospheric Observatory (SOHO) and, most recently, the Solar Terrestrial R...

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Autores principales: Goussies, N.A., Mejail, M.E., Jacobo, J., Stenborg, G.
Formato: JOUR
Materias:
Coronal mass ejections
Level sets
Supervised segmentation
Texture
Co-occurrence-matrix
Coronal mass ejection
Detection and tracking
Level Set
Level set implementation
Motion equations
Novel methods
Region competition
Solar and heliospheric observatories
Solar-terrestrial relations
Texture information
White light
Boundary layer flow
Buildings
Competition
Equations of motion
Observatories
Textures
Level measurement
Acceso en línea:http://hdl.handle.net/20.500.12110/paper_01678655_v31_n6_p496_Goussies
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
id todo:paper_01678655_v31_n6_p496_Goussies
record_format dspace
spelling todo:paper_01678655_v31_n6_p496_Goussies2023-10-03T15:05:25Z Detection and tracking of coronal mass ejections based on supervised segmentation and level set Goussies, N.A. Mejail, M.E. Jacobo, J. Stenborg, G. Coronal mass ejections Level sets Supervised segmentation Texture Co-occurrence-matrix Coronal mass ejection Detection and tracking Level Set Level set implementation Motion equations Novel methods Region competition Solar and heliospheric observatories Solar-terrestrial relations Supervised segmentation Texture information White light Boundary layer flow Buildings Competition Equations of motion Observatories Textures Level measurement Coronal mass ejection (CME) events refer to the appearance of a new, discrete, white-light feature (with outward velocity) in a coronagraph. The huge amount of data provided by the pertinent instruments onboard the Solar and Heliospheric Observatory (SOHO) and, most recently, the Solar Terrestrial Relations Observatory (STEREO) makes the human-based detection of such events excessively time consuming. Although several algorithms have been proposed to address this issue, there is still lack of universal consensus about their reliability. This work presents a novel method for the detection and tracking of CMEs as recorded by the LASCO instruments onboard SOHO. The algorithm we developed is based on level set and region competition methods, the CMEs texture being characterized by their co-occurrence matrix. The texture information is introduced in the region competition motion equations, and in order to evolve the curve, a fast level set implementation is used. © 2009 Elsevier B.V. All rights reserved. Fil:Mejail, M.E. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Stenborg, G. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. JOUR info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_01678655_v31_n6_p496_Goussies
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic Coronal mass ejections
Level sets
Supervised segmentation
Texture
Co-occurrence-matrix
Coronal mass ejection
Detection and tracking
Level Set
Level set implementation
Motion equations
Novel methods
Region competition
Solar and heliospheric observatories
Solar-terrestrial relations
Supervised segmentation
Texture information
White light
Boundary layer flow
Buildings
Competition
Equations of motion
Observatories
Textures
Level measurement
spellingShingle Coronal mass ejections
Level sets
Supervised segmentation
Texture
Co-occurrence-matrix
Coronal mass ejection
Detection and tracking
Level Set
Level set implementation
Motion equations
Novel methods
Region competition
Solar and heliospheric observatories
Solar-terrestrial relations
Supervised segmentation
Texture information
White light
Boundary layer flow
Buildings
Competition
Equations of motion
Observatories
Textures
Level measurement
Goussies, N.A.
Mejail, M.E.
Jacobo, J.
Stenborg, G.
Detection and tracking of coronal mass ejections based on supervised segmentation and level set
topic_facet Coronal mass ejections
Level sets
Supervised segmentation
Texture
Co-occurrence-matrix
Coronal mass ejection
Detection and tracking
Level Set
Level set implementation
Motion equations
Novel methods
Region competition
Solar and heliospheric observatories
Solar-terrestrial relations
Supervised segmentation
Texture information
White light
Boundary layer flow
Buildings
Competition
Equations of motion
Observatories
Textures
Level measurement
description Coronal mass ejection (CME) events refer to the appearance of a new, discrete, white-light feature (with outward velocity) in a coronagraph. The huge amount of data provided by the pertinent instruments onboard the Solar and Heliospheric Observatory (SOHO) and, most recently, the Solar Terrestrial Relations Observatory (STEREO) makes the human-based detection of such events excessively time consuming. Although several algorithms have been proposed to address this issue, there is still lack of universal consensus about their reliability. This work presents a novel method for the detection and tracking of CMEs as recorded by the LASCO instruments onboard SOHO. The algorithm we developed is based on level set and region competition methods, the CMEs texture being characterized by their co-occurrence matrix. The texture information is introduced in the region competition motion equations, and in order to evolve the curve, a fast level set implementation is used. © 2009 Elsevier B.V. All rights reserved.
format JOUR
author Goussies, N.A.
Mejail, M.E.
Jacobo, J.
Stenborg, G.
author_facet Goussies, N.A.
Mejail, M.E.
Jacobo, J.
Stenborg, G.
author_sort Goussies, N.A.
title Detection and tracking of coronal mass ejections based on supervised segmentation and level set
title_short Detection and tracking of coronal mass ejections based on supervised segmentation and level set
title_full Detection and tracking of coronal mass ejections based on supervised segmentation and level set
title_fullStr Detection and tracking of coronal mass ejections based on supervised segmentation and level set
title_full_unstemmed Detection and tracking of coronal mass ejections based on supervised segmentation and level set
title_sort detection and tracking of coronal mass ejections based on supervised segmentation and level set
url http://hdl.handle.net/20.500.12110/paper_01678655_v31_n6_p496_Goussies
work_keys_str_mv AT goussiesna detectionandtrackingofcoronalmassejectionsbasedonsupervisedsegmentationandlevelset
AT mejailme detectionandtrackingofcoronalmassejectionsbasedonsupervisedsegmentationandlevelset
AT jacoboj detectionandtrackingofcoronalmassejectionsbasedonsupervisedsegmentationandlevelset
AT stenborgg detectionandtrackingofcoronalmassejectionsbasedonsupervisedsegmentationandlevelset
_version_ 1782028138826432512

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