An automated approach to bloodstain pattern characterisation

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dc.contributor.advisor Taylor, M en
dc.contributor.advisor Elliot, D en
dc.contributor.advisor de Bruin, K en
dc.contributor.author Arthur, Ravishka en
dc.date.accessioned 2019-01-22T03:51:26Z en
dc.date.issued 2018 en
dc.identifier.uri http://hdl.handle.net/2292/45110 en
dc.description.abstract The discipline of Bloodstain Pattern Analysis (BPA) is founded on the visual evaluation of the diagnostic properties of bloodstain patterns and an interpretation of the mechanistic cause(s) leading up to their deposition at scenes of violent crime. The lack of objective bloodstain pattern measures and the often subjective opinions of bloodstain pattern analysts are among some of the main criticisms of the discipline. It is also argued, that the process of characterising the main properties of a bloodstain pattern is tantamount to assigning a cause to the bloodstain pattern. These persisting issues reflect the dire need for an established and discipline-standard BPA methodology. In light of this, an argument exists for the development of a completely new method of bloodstain pattern characterisation, that is based on objective and measurable pattern features. In this thesis, it is proposed that leveraging on technology could potentially assist with the development of specific solutions to problems associated with the interpretation of bloodstain patterns. To that end, the role of digital image-processing, eye tracking technology and pattern recognition were each considered in three important areas of bloodstain pattern characterisation. These areas were: data collection, understanding the mindset of the BPA analyst and the development of an automated bloodstain pattern recognition system. One of the major outcomes of this research, and an original contribution to the discipline, is the validation of an automated system capable of distinguishing bloodstain patterns. This system is fundamentally reliant on the extraction of bloodstain pattern features. Upto now, this has remained a process confined to the opinions and subjective experience of a bloodstain pattern analyst. These features, based on common spatter bloodstain pattern properties, were extracted using a comprehensive image-processing methodology. It is noteworthy to mention that this thesis provides a unique insight into the mindset of the bloodstain pattern analyst. To do this, eye tracking technology was used to capture the viewing behaviour of BPA analysts during a pattern classification task. The eye tracking study demonstrated that BPA analysts tend to focus greater attention on distinct regions of a bloodstain pattern. It is shown that these regions may reflect properties that are crucial in forming a pattern classification. An understanding of the properties as they related to these diagnostic regions formed an important outcome of this study. Overall, this research exposes the immense possibilities that technology could contribute to improving objectivity and consistency in the discipline. en
dc.publisher ResearchSpace@Auckland en
dc.relation.ispartof PhD Thesis - University of Auckland en
dc.relation.isreferencedby UoA99265119911102091 en
dc.rights Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. en
dc.rights.uri https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm en
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/nz/ en
dc.title An automated approach to bloodstain pattern characterisation en
dc.type Thesis en
thesis.degree.discipline Forensic Science en
thesis.degree.grantor The University of Auckland en
thesis.degree.level Doctoral en
thesis.degree.name PhD en
dc.rights.holder Copyright: The author en
dc.rights.accessrights http://purl.org/eprint/accessRights/OpenAccess en
pubs.elements-id 760055 en
pubs.record-created-at-source-date 2019-01-22 en


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http://creativecommons.org/licenses/by-nc-nd/3.0/nz/ Except where otherwise noted, this item's license is described as http://creativecommons.org/licenses/by-nc-nd/3.0/nz/

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