The CYGNO experiment aims to study rare events related to the search for low-mass Dark Matter and solar neutrino events. One of the main components of background comes from cosmic rays that generate long tracks in the detector's images. The interaction of such particles with the gas releases a variable energy profile along its trajectory to form tracks with multiple cores that can be easily reconstructed erroneously by being split into more than one cluster. Thus, this work offers a newly adapted version of the well-known DBSCAN algorithm, called iDDBSCAN, which exploits the directional characteristics of the clusters found by the DBSCAN to improve its clustering efficiency when dealing with multi-core tracks. A description of this algorithm is given in this paper, including validation of its parameters and assessment of its impact when included in the event selection routine of the experiment. To generate background events, data acquisition was performed with the detector installed in an overground laboratory, leaving it exposed to natural radiation. As a signal of interest, important to characterize many aspects of the detection system in the low energy region, a 55Fe source was used. The achieved results showed that the iDDBSCAN algorithm is capable of improving the background rejection of the experiment, through a more accurate reconstruction of the tracks produced by natural radiation such as cosmic rays, without deteriorating its signal detection efficiency and energy estimation.