Applying Density-based Clustering for Bloodstain Pattern Analysis

Bloodstain Pattern Analysis (BPA) is used by forensic officers to analyse bloodstains left at crime scenes. As a consequence, it has a crucial role in the investigations of bloody crimes. Currently, BPA activities are performed manually by leading to a slow and potentially imprecise analysis of the crime scenes. In order to overcome these issues, recently, some software tools have been developed in order to support forensic investigators in performing BPA activities in a more objective and fast way. However, only few approaches in literature use artificial intelligence methodologies to achieve this goal. Starting from this consideration, this paper presents a new intelligent tool based, for the first time, on the Density-Based Spatial Clustering of Application with Noise (DBSCAN) for supporting BPA activities. As shown in a case study, the proposed intelligent tool produces results that match with the ground truth.