HemoVision: An automated and virtual approach to bloodstain pattern analysis. (June 2015)

• Record Type: Journal Article
• Authors: Joris, Philip; Develter, Wim; Jenar, Els; Suetens, Paul; Vandermeulen, Dirk; Van de Voorde, Wim; Claes, Peter
• Is Part Of: Forensic science international. Volume 251(2015)
• Page Start: 116
• Page End: 123
• Publication Date: 2015-06
• Subjects: Bloodstain pattern analysis -- Automated -- Virtual -- HemoVision; Medical jurisprudence -- Periodicals; Chemistry, Forensic -- Periodicals; Forensic Medicine -- Periodicals; Médecine légale -- Périodiques; Chimie légale -- Périodiques; Gerechtelijke geneeskunde; Gerechtelijke chemie; Gerechtelijke psychiatrie; Chemistry, Forensic; Medical jurisprudence; Electronic journals; Periodicals; Electronic journals; 614.1
• DOI: 10.1016/j.forsciint.2015.03.018
• Languages: English
• ISSNs: 0379-0738

Abstract

Highlights: Traditional approaches to BPA are tedious and time consuming. Current virtual methods still require substantial user input. We propose a new approach using fiducial markers and computer vision algorithms. The proposed approach requires little user input while retaining accuracy. Fast analysis and practical advantages make this method a valuable update. Abstract: Bloodstain pattern analysis (BPA) is a subspecialty of forensic sciences, dealing with the analysis and interpretation of bloodstain patterns in crime scenes. The aim of BPA is uncovering new information about the actions that took place in a crime scene, potentially leading to a confirmation or refutation of a suspect's statement. A typical goal of BPA is to estimate the flight paths for a set of stains, followed by a directional analysis in order to estimate the area of origin for the stains. The traditional approach, referred to as stringing, consists of attaching a piece of string to each stain, and letting the string represent an approximation of the stain's flight path. Even though stringing has been used extensively, many (practical) downsides exist. We propose an automated and virtual approach, employing fiducial markers and digital images. By automatically reconstructing a single coordinate frame from several images, limited user input is required. Synthetic crime scenes were created and analysed in order to evaluate the approach. Results demonstrate the correct operation and practical advantages, suggesting that the proposed approach may become a valuable asset for practically analysing bloodstain spatter patterns. Accompanying software called HemoVision is currently provided as a demonstrator and will be further developed for practical use in forensic investigations.