Extraction of Statistical Properties of Solar Coronal Loops From Images of the Solar Dynamics Observatory Space Telescope

Coronal loops ExtremeUltraViolet (EUV) images provide us a lot of information about the structure of the chromospheres, the transition zone, the corona and the solar magnetic field. These structures are constantly moving and changing and the collected information from these images are too much such that in SDO reach to 1.6 TeraByte of data per day. This huge amount of information and images should be reduced and processed and this needs the development of the automated analysis tools of the solar images data. Especially investigation of the coronal loops needs exact extraction of them from the received images. In this paper we introduce and investigate the image processing methods, recognition and extraction of the coronal loops in active regions. We express the introductions regarding to trace patterns and features in digital images and present the recent studies about image processing methods and pattern recognition in solar physics. Afterwards we extract the coronal loops and develop the required techniques for that. These data, related tools and extended codes will be effective in various analysis of the coronal loops interactions.