Detection of Coronal Holes in Solar Disk Image Using Fast Fuzzy C-Means Algorithm

Detection of coronal holes (CHs) in the solar disk is one of the important tasks in the domain of astronomy. In this work, a technique based on image segmentation has been used for the detection of the CHs in the solar disk image. Here in the work, the task of image segmentation has been carried out using fast fuzzy c-means algorithm (FFCM). In the work, modified classical fuzzy c-means clustering technique has been induced for the segmentation of solar-disk image and detection of CHs in the image. For the purpose, the histogram of image intensities has been taken into account in order to faster the clustering and segmentation process. The output of the proposed algorithm has been compared visually with other existing technique of CHs detection in order to validate the capability of the proposed technique.