An image-processing methodology for extracting bloodstain pattern features. (August 2017)

• Record Type: Journal Article
• Authors: Arthur, Ravishka M.; Humburg, Philomena J.; Hoogenboom, Jerry; Baiker, Martin; Taylor, Michael C.; de Bruin, Karla G.
• Is Part Of: Forensic science international. Volume 277(2017)
• Page Start: 122
• Page End: 132
• Publication Date: 2017-08
• Subjects: Bloodstain Pattern Analysis -- Image-processing -- Forensic science -- Classification -- Local features -- Global features; 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.2017.05.022
• Languages: English
• ISSNs: 0379-0738

Abstract

Highlights: An image-processing methodology for analysing bloodstain patterns is proposed. Local and global features based on traditional spatter properties were extracted. Quantitative pattern data will enhance current bloodstain pattern taxonomies. Pattern data will enable analysts to reach objective pattern conclusions. This study lays the groundwork for an automated pattern classification system. Abstract: There is a growing trend in forensic science to develop methods to make forensic pattern comparison tasks more objective. This has generally involved the application of suitable image-processing methods to provide numerical data for identification or comparison. This paper outlines a unique image-processing methodology that can be utilised by analysts to generate reliable pattern data that will assist them in forming objective conclusions about a pattern. A range of features were defined and extracted from a laboratory-generated impact spatter pattern. These features were based in part on bloodstain properties commonly used in the analysis of spatter bloodstain patterns. The values of these features were consistent with properties reported qualitatively for such patterns. The image-processing method developed shows considerable promise as a way to establish measurable discriminating pattern criteria that are lacking in current bloodstain pattern taxonomies.