Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.754524
Title: The application of advanced metrology techniques to ballistics and toolmark identification
Author: Addinall, Katie Anne
ISNI:       0000 0004 7427 5605
Awarding Body: University of Huddersfield
Current Institution: University of Huddersfield
Date of Award: 2017
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Full text unavailable from EThOS. Thesis embargoed until 03 May 2023
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Abstract:
Since the early 1900s, the field of ballistic toolmark evidence has been developing as the instrumentation and computational power available has advanced. However, the use of these advanced techniques has not yet been validated for use in criminal proceedings. This has resulted in ballistic toolmark evidence being presented using the same techniques that have been employed for decades, unable to utilise more advanced techniques that have currently not been deemed acceptable in courts worldwide. Ballistic toolmark evidence currently relies on the use of comparison microscopy. Magnified optical 2D (greyscale) images of two separate surfaces are viewed side by side to ascertain the degree of similarity using visual comparison. Only highly trained expert examiners are able to carry out this comparison, and as such it is a time expensive method. The technique is built on subjective methodology, there are no mathematical outputs as the results are based on the opinion and experience of the expert examiner. With the advance of computational power and measurement techniques, it is now possible to create a digital system for the measurement and correlation of ballistic toolmark evidence. Evidence can be acquired as high density topographical datasets, and these datasets can be correlated against one another using mathematical algorithms, resulting in a comparison result based on a mathematical score or percentage match. Consequently, using these techniques could result in a more time efficient, repeatable and accurate system without problems of subjectivity or user bias. The novel contribution in this thesis has been shifting ballistic toolmark evidence and correlation from subjective and 2D qualitative methods to the use of the most advanced topographical areal datasets and mathematical correlation. A direct comparison of the efficacy of 2D digital and areal based systems was achieved, this showed that when the correct data is processed via the advanced system, there is a significant increase in the efficiency of hit list information. Novel contributions to these findings also include optimising the pre-processing of areal datasets, for both cartridge and bullets, and the effect of cartridge case materials on the overall topography of the toolmark. It was found that using current methods of data pre-processing resulted in a less efficient correlation system. For both bullets and cartridge cases however, using the developed preprocessing methods detailed in this thesis resulted in a more efficient method of correlation. Bullet correlation was also achieved using a full areal dataset of the toolmark, and such a method has not been published previously. Material analysis was attained across various cartridge manufacturers, which was then compared to the overall topography of the toolmark. It was found that differences in material composition would lead to differences in the topography of the toolmark. This is the first instance of such findings being published. Finally, a direct comparison of two separate advanced measurement systems was obtained, using the Alicona G4 focus variation instrument and the Alias ballistic imaging system. Using the same pre-processing methods for all datasets acquired, it was found that the quality of the dataset is significantly affected by the measurement method. Extraneous data such as optical spiking and data dropout was found to affect the efficacy of evidence correlation. This thesis presents the use of advanced methods for ballistic toolmark evidence, while considering issues with data fidelity, substrate material differences and pre-processing techniques.
Supervisor: Blunt, Liam ; Bills, Paul ; Jiang, Jane Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.754524  DOI: Not available
Keywords: TA Engineering (General). Civil engineering (General)
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