  This paper presents a new method to process the data recorded with muon
telescopes. We have developed this processing method for the plastic
scintillator-based hodoscopes located around the volcano La Soufri\`ere de
Guadeloupe, in the French Lesser Antilles, in order to perform muon
radiographies of the lava dome region, strongly impacted by the volcanic
hydrothermal activity. Our method relies on particle trajectory reconstruction,
performing a fit of the recorded hits in the impacted scintillator bars using a
Random Sample Consensus algorithm. This algorithm is specifically built to
discriminate outlier points, usually due to noise hits, in the data. Thus, it
is expected to significantly improve the signal/noise separation in muon track
hits and to obtain higher quality estimates of the particles' incident
trajectories in our detectors. The first analysis of the RANSAC-reconstructed
events offers promising results in terms of average density maps. To illustrate
the performances of this algorithm, we provide angular resolution and
reconstruction efficiency estimates using a GEANT4 simulation of a telescope
equipped with four detection matrices. In addition, we also show preliminary
results from open-sky data recorded with such telescope at La Soufri\`ere de
Guadeloupe volcano.
