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Proceedings Paper

Hyperspectral imaging of the crime scene for detection and identification of blood stains
Author(s): G. J. Edelman; T. G. van Leeuwen; M. C. G. Aalders
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Paper Abstract

Blood stains are an important source of information in forensic investigations. Extraction of DNA may lead to the identification of victims or suspects, while the blood stain pattern may reveal useful information for the reconstruction of a crime. Consequently, techniques for the detection and identification of blood stains are ideally non-destructive in order not to hamper both DNA and the blood stain pattern analysis. Currently, forensic investigators mainly detect and identify blood stains using chemical or optical methods, which are often either destructive or subject to human interpretation.

We demonstrated the feasibility of hyperspectral imaging of the crime scene to detect and identify blood stains remotely. Blood stains outside the human body comprise the main chromophores oxy-hemoglobin, methemoglobin and hemichrome. Consequently, the reflectance spectra of blood stains are influenced by the composite of the optical properties of the individual chromophores and the substrate. Using the coefficient of determination between a non-linear least squares multi-component fit and the measured spectra blood stains were successfully distinguished from other substances visually resembling blood (e.g. ketchup, red wine and lip stick) with a sensitivity of 100 % and a specificity of 85 %. The practical applicability of this technique was demonstrated at a mock crime scene, where blood stains were successfully identified automatically.

Paper Details

Date Published: 18 May 2013
PDF: 7 pages
Proc. SPIE 8743, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIX, 87430A (18 May 2013); doi: 10.1117/12.2021509
Show Author Affiliations
G. J. Edelman, Academisch Medisch Ctr. (Netherlands)
T. G. van Leeuwen, Academisch Medisch Ctr. (Netherlands)
M. C. G. Aalders, Academisch Medisch Ctr. (Netherlands)


Published in SPIE Proceedings Vol. 8743:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIX
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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