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On the spectroscopic examination of printed documents by using a field emission scanning electron microscope with energy-dispersive X-ray spectroscopy (FE-SEM-EDS) and chemometric methods: application in forensic science.
Verma, Neha; Sharma, Vishal; Kumar, Raj; Sharma, R; Joshi, M C; Umapathy, G R; Ohja, Sunil; Chopra, Sundeep.
Affiliation
  • Verma N; Institute of Forensic Science and Criminology, Panjab University, Chandigarh, 160014, India.
  • Sharma V; DFSS Fellow, Central Forensic Science Laboratory (Document Division), Chandigarh, 160036, India.
  • Kumar R; Institute of Forensic Science and Criminology, Panjab University, Chandigarh, 160014, India. vsharma@pu.ac.in.
  • Sharma R; Institute of Forensic Science and Criminology, Panjab University, Chandigarh, 160014, India.
  • Joshi MC; DFSS, Central Forensic Science Laboratory (Document Division), Bhopal, 462003, India.
  • Umapathy GR; DFSS, GEQD, Central Forensic Science Laboratory, Shimla, 171003, India.
  • Ohja S; Inter University Accelerator Centre, Aruna Asaf Ali Marg, New Delhi, 110 067, India.
  • Chopra S; Inter University Accelerator Centre, Aruna Asaf Ali Marg, New Delhi, 110 067, India.
Anal Bioanal Chem ; 411(16): 3477-3495, 2019 Jun.
Article in En | MEDLINE | ID: mdl-31093696
ABSTRACT
The detection of computer-generated document forgeries has always been a challenging task for forensic document examiners (FDE). With the aim to support the examination processes, Schottky field emission scanning electron microscopy with energy-dispersive X-ray spectroscopy (FE-SEM-EDS) is explored as a recent tool to analyze black toners obtained from laser printers and photocopier machines. Forty samples each from the laser printer and photocopier machines are procured and studied for morphological features, elemental profile, and multivariate analysis. The acquired SEM images and spectra are evaluated to discriminate and classify the toners having a different source of origin. Multivariate analysis is applied to develop a model of classification to successfully classify the printed documents on the basis of the similarities and differences in their composition. Hierarchical cluster analysis (HCA) discriminates the printouts in the forms of groups based on their chemical composition. The laser printer and the photocopier printed documents are grouped into 11 and eight clusters, respectively, based on their elemental composition. Cross-validation is further conducted to assess the capabilities of developed principal component analysis (PCA) and linear discriminant analysis (LDA) models for the examination of printouts from unknown origin. Graphical abstract.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Anal Bioanal Chem Year: 2019 Document type: Article Affiliation country: India

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Anal Bioanal Chem Year: 2019 Document type: Article Affiliation country: India