Firearms Identification Using Pattern Analysis and Computational Modeling.

Abstract

This paper describes a computational approach to the analysis of firearms forensic images, in particular, bullet images. Expended bullets usually bear characteristic surface markings associated with the mechanisms of the firearm that fired them. The traditional method of comparing bullet and cartridge markings involves the labor-intensive process of visual identification through a comparison microscope. This project proposes that the same process can be duplicated, and accelerated, using a low-cost video imaging and image processing system. The development of this project requires three important phases - "collection", "processing", and "analysis". In a laboratory scenario, the "barcodes" of the crime bullet and test bullet images are matched against each other. The barcode of the crime bullet is also matched against the barcodes of other potentially similar bullet images from the image database. A probability of match is generated for each comparison, and bullet images with a low probability of match are ignored. This effectively reduces the firearms examiner's workload. The bullet images with a high probability of match are retrieved, and displayed simultaneously to confirm the match.

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Document Details

Document Type
Technical Report
Publication Date
May 09, 1995
Accession Number
ADA299050

Entities

People

  • Foo S. Jiong

Organizations

  • United States Naval Academy

Tags

Communities of Interest

  • Biomedical
  • Energy and Power Technologies
  • Weapons Technologies

DTIC Thesaurus Topics

  • Change Detection
  • Computational Modeling
  • Computer Graphics
  • Computer Programming
  • Computer Programs
  • Computers
  • Detection
  • Detectors
  • Digital Image Processing
  • Identification
  • Identification Systems
  • Image Processing
  • Information Processing
  • Machine Perception
  • Operating Systems
  • United States
  • United States Naval Academy

Readers

  • Computer Science/Computer Engineering/Data Science/Digital Signal Processing.
  • Computer Vision.
  • Marksmanship and Weaponry.