An Automatic Method for Identification of Solar Coronal Loops

Safari Hossein, safari@znu.ac.ir, Department of Physics, University of Zanjan, Zanjan, Iran
Taran Somayeh, Department of Physics, University of Zanjan, Zanjan, Iran

Abstract
Identification of solar coronal loops from EUV images is a key process in data analysis and corona seismology. Here, we described a method for an automatic identification and tracking of the loops from images using a feature based classifier. The method is demonstrated using sequences of 171\AA\ images taken by SDO/AIA. The moments of loops are distinctive enough to be separated using an Probabilistic Neural Network (PNN) classifier.