Forensic classification of black inkjet prints using Fourier transform near-infrared spectroscopy and Linear Discriminant Analysis.
This work presents a study regarding the forensic discrimination of black inkjet-printed documents in question. Nondestructive Fourier transform near-infrared (FT-NIR) spectroscopy in combination with supervised classification method Discriminant Analysis (DA); Linear Discriminant Analysis (LDA) and...
| Publicado en: | Forensic Science International Vol. 299; pp. 128 - 135 |
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| Autores principales: | , , , , |
| Formato: | Journal Article |
| Publicado: |
Elsevier B.V.
Jun2019
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=136660658&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 136660658 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 03790738 3L0 jtl: Forensic Science International issn: 03790738 maglogo: N pubinfo: dt: Jun2019 vid: 299 pid: 82545 pub: Elsevier B.V. place: Philadelphia, Pennsylvania artinfo: ui: 136660658 136660658 NLM30991211 10.1016/j.forsciint.2019.03.041 NLM30991211 136660658 ppf: 128 ppct: 7 formats: tig: atl: Forensic classification of black inkjet prints using Fourier transform near-infrared spectroscopy and Linear Discriminant Analysis. aug: au: Oravec, Michal Beganović, Anel Gál, Lukáš Čeppan, Michal Huck, Christian W. affil: Slovak University of Technology in Bratislava, Faculty of Chemical and Food Technology, Radlinskeho 9, 812 37 Bratislava, Slovak Republic sug: ab: This work presents a study regarding the forensic discrimination of black inkjet-printed documents in question. Nondestructive Fourier transform near-infrared (FT-NIR) spectroscopy in combination with supervised classification method Discriminant Analysis (DA); Linear Discriminant Analysis (LDA) and Quadratic Discriminant Analysis (QDA) were utilized to investigate 22 different prints of the three most sold office printer brands. The spectra were acquired using the FT-NIR spectrometer NIRFlex N-500 (Büchi Labortechnik AG, Flawil, Switzerland) with the Fiber Optic Solids measuring cell in the spectral region of 10,000-4000 cm-1. Each sample was printed on the same type of office paper. The spectra were 45 times acquired on 3 separate printed squares of each sample. It results in 990 acquired spectra for the presented experiment. The FT-NIR spectra of the printed squares were split into calibration and test sets with which the Classification accuracy (CA) value of unknown samples was evaluated. In order to increase the significance, three different compilations of calibration and test sets were realized. The performance of three different Discriminant model methods; LDA (Euclidean and Mahalanobis algorithm) and QDA were compared to each other. Furthermore, the CA of each DA method was examined using 1-5 principal components (PCs) in the construction of the respective DA model. Two groups of models, according to the ink subset (Carbon black and Black colorant), were performed in raw and Standard Normal Variate (SNV) correction spectra alternations. The results showed that the Euclidean method yielded the highest accuracy in predicting independent test samples and thus clearly outperformed the QDA and Mahalanobis algorithm DA method. It was also determined that the ink type Carbon black had higher CA values than the ink type Black colorant. This work demonstrated the special ability of FT-NIR spectroscopy in combination with DA to examine inkjet-printed documents in a fast and non-destructive fashion. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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