Automatic detection of Coronal Mass Ejections using Computer Vision.

Details Automatic detection of Coronal Mass Ejections using Computer Vision. Automatic detection of Coronal Mass Ejections using Computer Vision.

May 2006

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2006agusmsh43a..02o&link_type=abstract

American Geophysical Union, Fall Meeting 2007, abstract #SH43A-02

Physics

7513 Coronal Mass Ejections (2101), 2101 Coronal Mass Ejections (7513)

Scientific paper

We present a software tool that automatically detects Coronal Mass Ejections (CMEs) as observed by the LASCO C2 instrument on board the SOHO spacecraft. The software developed follows a simple algorithm, which is based on decomposing 2-D Coronagraph images to 1-D and looking for outstanding bright regions. Thresholds determine these regions, and in time sequences, CMEs can be located and tracked. We have applied this method on a 12-month period of LASCO C2 data and have found about 75% more events than the NRL-GSFC-CUA CME catalog generated by human visual inspection. The automatic method gives a true positive rate of approximately 75% using the manual catalog as a benchmark. The software being presented is to be part a suite of software tools in the Solar Eruptive Event Detection System (SEEDS), being developed at George Mason University. The main purpose of SEEDS is to make associations of solar transient events observed by different instruments based on high-dimensional temporal and spatial data. An example problem SEEDS may be able to answer is whether or not a CME event seen In a Coronagraph is associated with a flareing/dimming event seen in coronal images. With many future spac missions underway, such as STEREO and SDO, SEEDS hopes to be utilized in aiding to the gain of scientific knowledge in an efficient and effective way, to the ultimate goal of making real time forecasting of space weather events.

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