Automatic firearm class identification from cartridge cases

Sridharan Kamalakannan, Christopher J. Mann, Philip R. Bingham, Thomas P. Karnowski, Shaun S. Gleason

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

We present a machine vision system for automatic identification of the class of firearms by extracting and analyzing two significant properties from spent cartridge cases, namely the Firing Pin Impression (FPI) and the Firing Pin Aperture Outline (FPAO). Within the framework of the proposed machine vision system, a white light interferometer is employed to image the head of the spent cartridge cases. As a first step of the algorithmic procedure, the Primer Surface Area (PSA) is detected using a circular Hough transform. Once the PSA is detected, a customized statistical region-based parametric active contour model is initialized around the center of the PSA and evolved to segment the FPI. Subsequently, the scaled version of the segmented FPI is used to initialize a customized Mumford-Shah based level set model in order to segment the FPAO. Once the shapes of FPI and FPAO are extracted, a shape-based level set method is used in order to compare these extracted shapes to an annotated dataset of FPIs and FPAOs from varied firearm types. A total of 74 cartridge case images non-uniformly distributed over five different firearms are processed using the aforementioned scheme and the promising nature of the results (95% classification accuracy) demonstrate the efficacy of the proposed approach.

Original languageEnglish (US)
Title of host publicationImage Processing
Subtitle of host publicationMachine Vision Applications IV
DOIs
StatePublished - Apr 1 2011
Externally publishedYes
EventImage Processing: Machine Vision Applications IV - San Francisco, CA, United States
Duration: Jan 25 2011Jan 27 2011

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume7877
ISSN (Print)0277-786X

Other

OtherImage Processing: Machine Vision Applications IV
CountryUnited States
CitySan Francisco, CA
Period1/25/111/27/11

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Keywords

  • Active Contours
  • Firing Pin Aperture
  • Firing Pin Impression
  • Image Segmentation
  • Level Set

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

Cite this

Kamalakannan, S., Mann, C. J., Bingham, P. R., Karnowski, T. P., & Gleason, S. S. (2011). Automatic firearm class identification from cartridge cases. In Image Processing: Machine Vision Applications IV [78770P] (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 7877). https://doi.org/10.1117/12.872414