Calculation of bloodstain impact angles using an Active Bloodstain Shape Model

• Traditional ellipse fitting is tedious, subjective and based on a simplification of the stain formation process. In addition, experiments have shown that the inverse sine may fail to accurately model width–length ratios.
• We propose a data-driven approach, using an Active Shape Model and polynomial regression, implicitly incorporating the intricate interactions between the blood and the target surface.
• The proposed approach has higher accuracy compared to automatic ellipse fitting.
• The proposed approach is faster and more objective than manual analyses.

ObjectivesTraditional Bloodstain Pattern Analysis (BPA) estimates impact angles for bloodstain spatters by employing ellipses and an inverse sine. This approach is based upon a simplification of the stain formation process, and ignores the physical properties of blood, and its intricate interactions with the target surface. This research presents a data-driven approach, starting from experimental bloodstain spatters. No assumptions about the shape of stains or about the relation between the shape and their impact angle are made a priori.Materials and methodsExperimental bloodstain data is gathered, after which shape variations are extracted by employing an Active Shape Model. A non-linear regression is then used to explain the relation between stain shape and impact angle.ResultsExperimental results show that traditional width–length ratios may deviate from the assumed inverse sine. The proposed approach, on the other hand, closely follows the experimental data through its regression. Additional experiments have shown an increased accuracy on impact angle estimates for the proposed approach when compared to automatic ellipse fitting.ConclusionThe proposed method performs better than automatic ellipse fitting. The higher accuracy and faster and more objective analysis suggest that the developed model is applicable in real-life scenarios, and can provide a valuable update to Bloodstain Pattern Analysis.