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Computer Vision in Analyzing the Propagation of a Gas-Gunpowder Jet.

Irina G Palchikova1, Igor V Latyshov2, Evgenii S Smirnov1

  • 1Technological Design Institute of Scientific Instrument Engineering of the Siberian Branch of the RAS, 630058 Novosibirsk, Russia.

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A new method uses digital image analysis to quantify gunshot residue (GSR) on targets. This technique accurately estimates GSR amount and distribution, aiding forensic investigations.

Keywords:
digital image processinggas–gunpowder jetgunshot residuesoptical densitytarget

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Area of Science:

  • Forensic Science
  • Image Analysis
  • Ballistics

Background:

  • Gunshot residue (GSR) analysis is crucial in forensic investigations.
  • Quantifying GSR deposition patterns provides valuable information about shooting incidents.
  • Current methods for GSR analysis can be time-consuming and subjective.

Purpose of the Study:

  • To develop and validate a mathematical method for processing digital target images.
  • To enable quantitative estimation of GSR amount and distribution from digital images.
  • To provide a reliable tool for analyzing GSR patterns in forensic ballistics.

Main Methods:

  • Mathematical processing of digital target images.
  • Analysis of optical density in concentric rings and sectors of target images.
  • Correlation of integral optical density with deposited GSR mass.
  • Quantification of radial and angular GSR distribution variations.

Main Results:

  • Demonstrated the possibility of estimating GSR amount and distribution using digital image analysis.
  • Revealed radial and angular dependence of soot distribution in gas-gunpowder jets.
  • Established that integral optical density correlates with GSR mass on the target.
  • Enabled quantification of GSR layer thickness differences based on weapon type and distance.

Conclusions:

  • Digital image processing offers a robust method for GSR quantification.
  • The developed technique allows for detailed analysis of GSR deposition patterns.
  • This method enhances the ability to differentiate shooting scenarios based on GSR evidence.