Paper
5 June 2014 The challenges of analysing blood stains with hyperspectral imaging
J. Kuula, H.-H. Puupponen, H. Rinta, I. Pölönen
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Abstract
Hyperspectral imaging is a potential noninvasive technology for detecting, separating and identifying various substances. In the forensic and military medicine and other CBRNE related use it could be a potential method for analyzing blood and for scanning other human based fluids. For example, it would be valuable to easily detect whether some traces of blood are from one or more persons or if there are some irrelevant substances or anomalies in the blood. This article represents an experiment of separating four persons' blood stains on a white cotton fabric with a SWIR hyperspectral camera and FT-NIR spectrometer. Each tested sample includes standardized 75 _l of 100 % blood. The results suggest that on the basis of the amount of erythrocytes in the blood, different people's blood might be separable by hyperspectral analysis. And, referring to the indication given by erythrocytes, there might be a possibility to find some other traces in the blood as well. However, these assumptions need to be verified with wider tests, as the number of samples in the study was small. According to the study there also seems to be several biological, chemical and physical factors which affect alone and together on the hyperspectral analyzing results of blood on fabric textures, and these factors need to be considered before making any further conclusions on the analysis of blood on various materials.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
J. Kuula, H.-H. Puupponen, H. Rinta, and I. Pölönen "The challenges of analysing blood stains with hyperspectral imaging", Proc. SPIE 9112, Sensing Technologies for Global Health, Military Medicine, and Environmental Monitoring IV, 91120W (5 June 2014); https://doi.org/10.1117/12.2050180
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KEYWORDS
Blood

Hyperspectral imaging

Biological research

Chemical analysis

Short wave infrared radiation

Spectroscopy

Statistical analysis

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