Automatic Extraction of Filaments in Hα Solar Images

Abstract

This paper presents a new method which allows for the automatic extraction and tracking of the evolution of filaments in solar images. Series of Hα full-disk images are taken in regular time intervals to observe the changes of the solar disk features. In each picture, the solar chromosphere filaments are identified for further evolution examination. Two alternative preprocessing techniques converting grayscale images into black-and-white pictures with enhanced chromosphere granularity are examined: local thresholding based on median values and global thresholding with brightness and area normalization. The next step employs morphological closing operations with multi-directional linear structuring elements to extract elongated shapes in the image. After logical intersection of directional filtering results, remaining noise is removed from the final outcome using morphological dilation and erosion with a circular structuring element. Experimental results show that the developed technique can achieve excellent results in detecting large filaments and good detection rates for small filaments.