Filament Recognition In Solar Images With The Neural Network Technique

Details Filament Recognition In Solar Images With The Neural Network Technique Filament Recognition In Solar Images With The Neural Network Technique

May 2005

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2005soph..228..137z&link_type=abstract

Solar Physics, Volume 228, Issue 1-2, pp. 137-148

Physics

9

Scientific paper

We describe a new technique developed for an automated recognition of solar filaments visible in Hα hydrogen line full-disk spectroheliograms. These filaments are difficult to recognize because of variability in the background caused by atmospheric conditions. The presented technique is based on an artificial neural network (ANN) consisting of two hidden neurons and one output neuron which learn to exclude the contribution of a changeable background to a filament. The ANN is trained on a single image fragment labeled manually to recognize the filament elements depicted on a local background. The background contribution is approximated with linear and parabolic functions. This technique applied to the filament recognition in 54 cropped images reveals better detection results for a parabolic approximation than for a linear one approaching an accuracy of about 82% of the total filament pixels.

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