The white light coronagraphs onboard SOHO (LASCO-C2 and -C3) and most recently STEREO (SECCHI -COR1 and -COR2) have detected a myriad of coronal mass ejections (CME). They are a key component of space weather and under certain conditions they can become geo-effective, hence the importance of their kinematic characterization to help predict their effects. However, there is still a lot of debate on how to define the event boundaries for space weather purposes, which in turn makes it difficult to agree on their kinematic properties. That lack of agreement is reflected in both the manual and automated CME catalogs in existence. To contribute to a more objective definition and characterization of white-light coronagraph events, Goussies et al. (2010) introduced recently the concept of “texture of the event”. Based on that property, they developed a supervised segmentation algorithm to allow the automatic tracking of dynamic events observed in the coronagraphs field of view, which is called CORonal SEgmentation Technique (CORSET). In this work, we have enhanced the capabilities of the algorithm by adding several new functionalities, namely the automatic computation of different morphological and kinematic parameters. We tested its performance on 57 well-studied limb CME events observed with the LASCO coronagraphs between 1997 and 2001, and compared the parameters obtained with those from three existent CME lists: two of them obtained from an observer-based detection and tracking method (i.e., two manual catalogs), and the other one based on the automated detection and characterization of the CME events (i.e., a fully automated catalog). We found that 51 events could be tracked and quantified in agreement with the CME definition. In general terms, the position angle, and the radial and expansion speeds are in agreement with the manual catalogs used for comparison. On the other hand, some discrepancies between CORSET and the automated catalog were found, which can be explained by the different delimitation of the CME angular extent.