Bloodstain pattern analysis: A new challenge for computational intelligence community

Bloodstain pattern analysis (BPA) is a forensic discipline that plays a key role in tracing events which caused a bloodshed at a crime scene. Indeed, BPA supports worldwide investigation agencies (US FBI, Italian Carabinieri and so on) in interpreting the morphology and distribution of bloodspots at a crime scene in order to enable a potentially complete reconstruction of the dynamics of the act of violence with a consequent identification of potential suspects for that crime. However, in spite of its importance, this forensic discipline is still based on completely manual approaches, making the analysis of a crime scene long, tedious and potentially imperfect. This position paper is aimed at proving that computational intelligence methodologies can be efficiently integrated with image processing techniques to support forensic investigators in increasing their performance in examining bloodstains, both in terms of time and accuracy of analysis. A preliminary study involving the application of fuzzy clustering has been carried out in order to validate our opinion and stimulate computational intelligence community to face this new challenge towards a formal definition of Forensic Intelligence.