A review of laser printer classification and identification.

Journal: Forensic science international
Published Date:

Abstract

Forensic document examination has long focused on elucidating the classification and identification paradigms of laser-printed documents. Toner establishes critical evidentiary linkages between printed documents and their corresponding printing devices, making toner analysis a significant part of document examination. This systematic review synthesizes contemporary advances in laser printer forensics through tripartite analytical dimensions: morphological analysis, physical characterization, and chemical profiling. The emerging paradigm demonstrates heightened adoption of quasi-nondestructive and nondestructive testing methodologies to maintain evidentiary integrity, concurrently with the integration of chemometric workflows and machine learning architectures to address operational demands for rapid, high-fidelity analysis. Our methodological framework facilitates comparative evaluation of analytical techniques' merits and limitations, supported by bibliometric analysis of peer-reviewed studies (2018-2024) that reveals emergent trends. Crucially, we identify a critical research gap in explainable artificial intelligence (XAI) frameworks for forensic algorithm validation, underscoring the imperative for interpretable computational models in judicial contexts.

Authors

  • Yawen Zhao
    East China University of Political Science and Law, 1575, Wanhangdu Road, Shanghai 200042, PR China; Academy of Forensic Science, 1347, West Guangfu Road, Shanghai 200063, PR China.
  • Xu Yang
    Department of Food Science and Technology, The Ohio State University, Columbus, OH, United States.
  • Xiaohong Chen
    Department of Neurology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.

Keywords

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