Literature DB >> 25498930

The application of visible wavelength reflectance hyperspectral imaging for the detection and identification of blood stains.

Bo Li1, Peter Beveridge1, William T O'Hare1, Meez Islam2.   

Abstract

Current methods of detection and identification of blood stains rely largely on visual examination followed by presumptive tests such as Kastle-Meyer, Leuco-malachite green or luminol. Although these tests are useful, they can produce false positives and can also have a negative impact on subsequent DNA tests. A novel application of visible wavelength reflectance hyperspectral imaging has been used for the detection and positive identification of blood stains in a non contact and non destructive manner on a range of coloured substrates. The identification of blood staining was based on the unique visible absorption spectrum of haemoglobin between 400 and 500 nm. Images illustrating successful discrimination of blood stains from nine red substances are included. It has also been possible to distinguish between blood and approximately 40 other reddish stains. The technique was also successfully used to detect latent blood stains deposited on white filter paper at dilutions of up to 1 in 512 folds and on red tissue at dilutions of up to 1 in 32 folds. Finally, in a blind trial, the method successfully detected and identified a total of 9 blood stains on a red T-shirt.
Copyright © 2014 Forensic Science Society. Published by Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Blood stain detection; Forensic science; Hyperspectral imaging; Liquid crystal tuneable filter

Mesh:

Year:  2014        PMID: 25498930     DOI: 10.1016/j.scijus.2014.05.003

Source DB:  PubMed          Journal:  Sci Justice        ISSN: 1355-0306            Impact factor:   2.124


  3 in total

1.  Reconstruction of crimes by infrared photography.

Authors:  V Sterzik; M Bohnert
Journal:  Int J Legal Med       Date:  2016-03-01       Impact factor: 2.686

2.  Detection of painted-over traces of blood and seminal fluid.

Authors:  V Barrera; C Haas; E A Meixner; B Fliss
Journal:  Int J Legal Med       Date:  2018-01-27       Impact factor: 2.686

3.  Blood Stain Classification with Hyperspectral Imaging and Deep Neural Networks.

Authors:  Kamil Książek; Michał Romaszewski; Przemysław Głomb; Bartosz Grabowski; Michał Cholewa
Journal:  Sensors (Basel)       Date:  2020-11-21       Impact factor: 3.576

  3 in total

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