No / We present an automated technique for comparison of magnetic field inversion-line maps from SOHO/MDI magnetograms with solar filament data from the Solar Feature Catalogue created as part of the European Grid of Solar Observations project. The Euclidean distance transform and connected component labelling are used to identify nearest inversion lines to filament skeletons. Several filament inversion-line characteristics are defined and used to automate the decision whether a particular filament/inversion-line pair is suitable for quantitative comparison of orientation and separation. The technique is tested on 551 filaments from 14 H¿ images at various dates, and the distributions of angles and distances between filament skeletons and line-of-sight (LOS) magnetic inversion lines are presented for six levels of magnetic field smoothing. The results showed the robustness of the developed technique which can be applied for a statistical analysis of magnetic field in the vicinity of filaments. The method accuracy is limited by the static filament detection which does not distinguish between filaments, fibrils, pre-condensations and filament barbs and this may increase the asymmetries in magnetic distributions and broadening in angular distributions that requires the incorporation of a feature tracking technique.

No / Robust techniques are developed to put the H and Ca K line full-disk images taken at the Meudon Observatory into a standardised form of a `virtual solar image'. The techniques include limb fitting, removal of geometrical distortion, centre position and size standardisation and intensity normalisation. The limb fitting starts with an initial estimate of the solar centre using raw 12-bit image data and then applies a Canny edge-detection routine. Candidate edge points for the limb are selected using a histogram based method and the chosen points fitted to a quadratic function by minimising the algebraic distance using SVD. The five parameters of the ellipse fitting the limb are extracted from the quadratic function. These parameters are used to define an affine transformation that transforms the image shape into a circle. Transformed images are generated using the nearest neighbour, bilinear or bicubic interpolation. Intensity renormalisation is also required because of a limb darkening and other non-radial intensity variations. It is achieved by fitting a background function in polar coordinates to a set of sample points having the median intensities and by standardising the average brightness. Representative examples of intermediate and final processed results are presented in addition to the algorithms developed. The research was done for the European Grid of Solar Observations (EGSO) project.

no / The Solar Feature Catalogues (SFCs) are created from digitized solar images using automated pattern recognition techniques developed in the European Grid of Solar Observation (EGSO) project. The techniques were applied for detection of sunspots, active regions and filaments in the automatically standardized full-disk solar images in Caii K1, Caii K3 and H¿ taken at the Meudon Observatory and white-light images and magnetograms from SOHO/MDI. The results of automated recognition are verified with the manual synoptic maps and available statistical data from other observatories that revealed high detection accuracy. A structured database of the Solar Feature Catalogues is built on the MySQL server for every feature from their recognized parameters and cross-referenced to the original observations. The SFCs are published on the Bradford University web site http://www.cyber.brad.ac.uk/egso/SFC/ with the pre-designed web pages for a search by time, size and location. The SFCs with 9 year coverage (1996¿2004) provide any possible information that can be extracted from full disk digital solar images. Thus information can be used for deeper investigation of the feature origin and association with other features for their automated classification and solar activity forecast.