The ability to objectify ballistic evidence is a challenge faced by firearms examiners around the world. A number of researchers are trying to improve bullet-identification systems to address the deficiencies in this regard and which were detailed within the National Academy of Sciences report (2009). Bullet to bullet comparisons have largely relied on the supposition that the rifling marks within the barrel of a weapon have class characteristics that identify a weapon type and individual characteristics that identify a specific weapon. Such characteristics are impressed onto projectiles when they are fired through a particular weapon and an examination of specific regions displaying striated marks on the projectiles allows for identification and comparison to be undertaken. This premise has been the foundation for comparative firearms examination for many decades. In many cases only small portions of striated regions of the projectile are examined and the process is essentially subjective. More recently focus has turned to making use of more sophisticated imaging modalities to view entire regions of the projectile and the development of automated systems for the comparison of the topographical surfaces recorded. Projectiles from a fired series of 609 pellets were examined using an Alicona infinite focus microscope. A mathematical methodology was developed to pre-process the resultant topographical maps generating point data for comparison. Comparisons between different data sets were undertaken using chemometric techniques (principal component analysis, hierarchical cluster analysis and linear discriminant analysis) to assess (1) the repeatability and reproducibility of the method, (2) the variability of land engraved areas (LEAs) in repetitively fired projectiles over a series of test fires, (3) the ability of the developed method to distinguish between different classes of weapons (pistols and rifles) and weapons within the same class (rifles) and (4) the ability of the method to correctly associate distorted projectiles to the weapon that fired them.The developed objective method still requires an operator to identify the LEAs to be scanned; however the mathematical alignments were objectively achieved. The discrimination of weapons by class was achieved although weapons within the same class could not be easily separated from each other. The LEAs on a single projectile varied in terms of distinction from each other and, while there was some variation with use of the same weapon over time, this was not pronounced. Generally the LEAs with more distinguishing features across the entire region created a better discriminating surface and in particular facilitated the correct association for distorted projectiles.
|Date of Award||15 Dec 2016|
- University Of Strathclyde
|Supervisor||Alison Nordon (Supervisor) & Lynn Dennany (Supervisor)|