Automated detection of CMEs

Physics

Scientific paper

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Sun: Corona, Sun: Particle Emission

Scientific paper

We have developed a shoftware package for 'Computer Aided CME Tracking' (CACTus), that autonomously detects CMEs in image sequences from LASCO. The crux of the CACTus software is the detection of CMEs as bright ridges in [height, time] maps using the Hough transform. The output is a list of events, similar to the classic catalogs, with principle angle, angular width and velocity estimation for each CME. In contrast to catalogs assembled by human operators, these CME detections by software can be faster and possibly also more objective, as the detection criterion is written explicitly in a program. In this paper we discuss two applications of the software. In a first application, we validate the performance by comparing the CACTus output with the classical, visually assembled CME catalogs. We discuss its present success rate (about 75%) and prospects for improvement. By giving an example we show that the software can also reveal CMEs that have been not been listed in the catalogs. Such unreported cases might be of influence on CME stastistics and prove that also the present catalogs do not have a 100% success rate. The second application, is an operational version of CACTus that scans in real time, the last available LASCO images for recent CMEs.

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