  We present a new method to automatically track filaments over the solar disk.
The filaments are first detected on Meudon Spectroheliograph H{\alpha} images
of the Sun, applying the technique developed by Fuller, Aboudarham, and Bentley
(Solar phys. 227, 61, 2005). This technique combines cleaning processes, image
segmentation based on region growing, and morphological parameter ex- traction,
including the determination of filament skeletons. The coordinates of the
skeleton pixels, given in a heliocentric system, are then converted to a more
appropriate reference frame that follows the rotation of the Sun surface. In
such a frame, a co-rotating filament is always located around the same
position, and its skeletons (extracted from each image) are thus spatially
close, forming a group of adjacent features. In a third step, the shape of each
skeleton is compared with its neighbours using a curve-matching algorithm. This
step will permit us to define the probability [P ] that two close filaments in
the co-rotating frame are actually the same one observed on two different
images. At the end, the pairs of features, for which the corresponding
probability is greater than a threshold value, are associated using tracking
identification indexes.On a representative sample of filaments, the good
agreement between automated and manual tracking confirms the reliability of the
technique to be applied on large data sets. Especially, this code is already
used in the framework of the Heliophysics Integrated Observatory (HELIO) to
populate a catalogue dedicated to solar and heliospheric features (HFC). An
extension of this method to others filament observations, and possibly the
sunspots, faculae, and coronal holes tracking can be also envisaged.
