A review of laser printer classification and identification.

Area of Science:

• Forensic Science
• Analytical Chemistry
• Computer Science

Background:

• Toner analysis is crucial for linking laser-printed documents to specific devices in forensic investigations.
• Traditional methods are evolving with new analytical techniques for enhanced evidentiary value.

Purpose of the Study:

• To systematically review contemporary advances in laser printer forensics.
• To evaluate analytical techniques for morphological, physical, and chemical characterization of toner.
• To identify trends and research gaps in the field.

Main Methods:

• Systematic review of peer-reviewed studies from 2018-2024.
• Bibliometric analysis to identify emergent trends.
• Evaluation of quasi-nondestructive and nondestructive testing methodologies.
• Integration of chemometric workflows and machine learning.

Main Results:

• Heightened adoption of quasi-nondestructive and nondestructive testing for evidentiary integrity.
• Integration of chemometrics and machine learning for rapid, high-fidelity analysis.
• Comparative evaluation of analytical techniques' strengths and weaknesses.

Conclusions:

• Forensic document examination is increasingly adopting advanced analytical and computational methods.
• There is a critical need for explainable artificial intelligence (XAI) frameworks in forensic algorithm validation.
• Interpretable computational models are imperative for judicial contexts in forensic science.