000003143 001__ 3143
000003143 005__ 20170124120117.0
000003143 037__ $$aSEMIN-2017-0017
000003143 100__ $$aBourgoignie, Bram
000003143 245__ $$aRecent developments of the CACTus CME detection software
000003143 260__ $$c2011
000003143 269__ $$c2011-01-20
000003143 520__ $$aThe Computer Aided CME tracking or CACTus for short is an algorithm used to detect coronal mass ejections automatically. The algorithm was first introduced in 2004 and since then it was often adapted and extended. Some major changes were recently made to the CACTus algorithm. A new cleaning algorithm was introduced and some small changes were made to optimize the detection. The new cleaning algorithm was originally developed for STEREO SECCHI-A and SECCHI-B images and is adapted for SOHO LASCO images. The algorithm detects bright features in images and based on characteristics we distinguish between bright features which are possibly CMEs and so called \'streaks\'. Streaks and bright points are removed from the image. Using the upgraded algorithm, we have constructed a second version of the CACTus LASCO CME catalog that is available online (including movies). To optimize further our thresholds we are doing a parameter study on various variables available through the fits-header. The average intensity of LASCO images shows a clear correlation with the sunspot number and with the seasons. In our future work we will try to estimate the influence of these variations on the CME detection performance.
000003143 594__ $$aNO
000003143 773__ $$tKULeuven
000003143 8560_ $$fbram.bourgoignie@observatoire.be
000003143 980__ $$aSEMIN