The estimation of the age of a blood stain using reflectance spectroscopy with a microspectrophotometer, spectral pre-processing and linear discriminant analysis

Abstract A novel method for the non-destructive age determination of a blood stain is described. It is based on the measurement of the visible reflectance spectrum of the haemoglobin component using a microspectrophotometer (MSP), spectral pre-processing and the application of supervised statistical...

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Veröffentlicht in:Forensic science international 2011-10, Vol.212 (1), p.198-204
Hauptverfasser: Li, Bo, Beveridge, Peter, O’Hare, William. T, Islam, Meez
Format: Artikel
Sprache:eng
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Zusammenfassung:Abstract A novel method for the non-destructive age determination of a blood stain is described. It is based on the measurement of the visible reflectance spectrum of the haemoglobin component using a microspectrophotometer (MSP), spectral pre-processing and the application of supervised statistical classification techniques. The reflectance spectra of sample equine blood stains deposited on a glazed white tile were recorded between 1 and 37 days, using an MSP at wavelengths between 442 nm and 585 nm, under controlled conditions. The determination of age was based on the progressive change of the spectra with the aging of the blood stain. These spectra were pre-processed to reduce the effects of baseline variations and sample scattering. Two feature selection methods based on calculation of Fisher's weights and Fourier transform (FT) of spectra were used to create inputs into a statistical model based on linear discriminant analysis (LDA). This was used to predict the age of the blood stain and tested by using the leave-one-out cross validation method. When the same blood stain was used to create the training and test datasets an excellent correct classification rate (CCR) of 91.5% was obtained for 20 input frequencies, improving to 99.2% for 66 input frequencies. A more realistic scenario where separate blood stains were used for the training and test datasets led to poorer successful classification due to problems with the choice of substrate but nevertheless up to 19 days a CCR of 54.7% with an average error of 0.71 days was obtained.
ISSN:0379-0738
1872-6283
DOI:10.1016/j.forsciint.2011.05.031