Solar image segmentation by use of mean field fast annealing

We present a "continuous” analysis of a solar image in order to address the problem of image segmentation. Our approach is based on combinatorial optimization methods and in particular on Mean Field Fast Annealing (MFFA). Mean-field theory gives a deterministic nature to our algorithm while its efficiency is improved by a fast cooling schedule. We show how this method can be used to separate efficiently the regions of different solar activity giving a tool for a future automated recognition and classification of sunspots.