Literature DB >> 26386337

Understanding the visibility of blood on dark surfaces: A practical evaluation of visible light, NIR, and SWIR imaging.

Tom G Schotman1, Antoinette A Westen1, Jaap van der Weerd1, Karla G de Bruin2.   

Abstract

Bloodstains on dark surfaces are often difficult to detect due to a lack of contrast. Infrared photography is in many cases a solution as it enhances the contrast between blood and background. Still, on some surfaces bloodstains cannot be visualized. In this study, we investigate why bloodstains on certain surfaces are not detected and how visibility can be improved. Bloodstains on 166 dark fabrics were photographed by four different cameras and for each, the visibility of the bloodstains was scored. The spectral properties of the dark fabrics were examined as well as the properties of the dyes used to colour the textiles. In addition, spreading of the blood within the textile and the roughness of the material were taken into account. In the investigated set of textiles, visibility of blood is mainly determined by the spectral properties of the textile dye. In addition, a high surface roughness of the textile reduces the visibility.
Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Keywords:  Blood; Bloodstain pattern analysis; Fabric; Infrared; Photography; Textile

Mesh:

Year:  2015        PMID: 26386337     DOI: 10.1016/j.forsciint.2015.08.024

Source DB:  PubMed          Journal:  Forensic Sci Int        ISSN: 0379-0738            Impact factor:   2.395


  2 in total

1.  Detectability, visualization, and DNA analysis of bloodstains after repainting the walls.

Authors:  Frank Ramsthaler; Julia Schlote; Axel Gehl; Sabine Cappel-Hoffmann; Mattias Kettner
Journal:  Int J Legal Med       Date:  2018-08-09       Impact factor: 2.686

2.  Large area imaging of forensic evidence with MA-XRF.

Authors:  Kirsten Langstraat; Alwin Knijnenberg; Gerda Edelman; Linda van de Merwe; Annelies van Loon; Joris Dik; Arian van Asten
Journal:  Sci Rep       Date:  2017-11-08       Impact factor: 4.379

  2 in total

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