• DocumentCode
    1325666
  • Title

    Characterisation of tool marks on cartridge cases by combining multiple images

  • Author

    Leloglu, Ugur Murat

  • Author_Institution
    TUBITAK UZAY, Ankara, Turkey
  • Volume
    6
  • Issue
    7
  • fYear
    2012
  • fDate
    10/1/2012 12:00:00 AM
  • Firstpage
    854
  • Lastpage
    862
  • Abstract
    The characteristic marks left by firearms on cartridge cases (CCs) during firing are used by forensic experts to identify CCs fired from the same firearm; however, the nature of the tool marks on the CCs is not well understood. The objective of this study is to separate the tool marks i.e., the signal, from the background signal and the noise and thereby understand its peculiarities. To extract the signal, which is much weaker than the noise, second-order derivatives of three-dimensional images of the surfaces of a series of CCs fired from the same firearm were used. Instead of using rigid body transformation, the images are first registered based on estimated planar homographies; then unwanted areas, including the headstamp are masked out. Aligned images are merged by weighted averaging using estimated signal and noise variances, which are also used for calculating signal and noise spectra. Wiener filtering is applied to further increase the signal-to-noise ratio. The effectiveness of the method is demonstrated on real data. It is also shown that breech face marks exist on the outer ring, a feature typically ignored in automatic matching. In addition, visual results obtained by reconstructing the surface from second-order derivatives are presented.
  • Keywords
    Wiener filters; image processing; law; military computing; weapons; CC; Wiener filtering; automatic matching; background signal; cartridge cases; firearm; forensic experts; noise spectra; noise variances; planar homographies estimation; second order derivatives; signal extraction; signal-to-noise ratio; three-dimensional images; tool mark characterisation;
  • fLanguage
    English
  • Journal_Title
    Image Processing, IET
  • Publisher
    iet
  • ISSN
    1751-9659
  • Type

    jour

  • DOI
    10.1049/iet-ipr.2011.0130
  • Filename
    6336956