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Inkjet-printed Polyvinyl Alcohol Multilayers
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Inkjet classification based on a few letters.

Xiao-Hong Chen1, Xu Yang1, Yi-Wen Luo1

  • 1Academy of Forensic Science, 1347, West Guangfu Road, Shanghai 200063, PR China.

Forensic Science International
|June 20, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces a new method to identify inkjet printer sources from just a few printed letters. This technique achieves high classification accuracy, aiding in forensic document examination.

Keywords:
Bayesian approachImage featuresInkjet printingPrintersQuestioned document examinationStatistical analysis

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Area of Science:

  • Forensic Science
  • Document Examination
  • Printer Forensics

Background:

  • Morphology-based inkjet document classification is cost-effective but requires extensive data.
  • Existing methods often need analysis of numerous printed characters.

Purpose of the Study:

  • To develop a novel method for detecting the source of printed documents using minimal printed letters.
  • To enable efficient identification of specific inkjet printers for tactical purposes.

Main Methods:

  • Collected data from 27 inkjet models (HP, Canon, Epson).
  • Utilized Principal Component Analysis (PCA) and Kernel Density Estimation (KDE).
  • Employed multivariate KDE for likelihood ratio computation and K-nearest neighbour analysis for classification.

Main Results:

  • Achieved classification accuracy as high as 98% using K-nearest neighbour analysis.
  • Demonstrated significant results in likelihood ratio evaluation (EER=0, RMEP=0, RMED=0.07).
  • Successfully identified specific inkjet printers from limited printed text.

Conclusions:

  • The proposed method accurately identifies inkjet printer sources using few printed characters.
  • This technique offers a highly efficient solution for forensic document analysis.
  • The findings have practical implications for tactical source detection in document examination.