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Measurement of human teeth characteristics using Biteprint© software

Chng, Andrea (2018) Measurement of human teeth characteristics using Biteprint© software. Masters by Research thesis, Murdoch University.

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Bite mark impression evidence in criminal investigation may be of significance in allegations of child abuse and/or sexual assault. It enables the possible identification of the individual responsible for leaving the bite mark on the skin based on the teeth characteristics. Careful recording and documentation of the bite mark must be undertaken to maintain evidentiary value.

Bite mark analysis is often used to include or exclude a person of interest regarding the source of the bite mark on the alleged victim, this is done by comparing the individual’s dentition to the bite mark as it was based on the assumption that each individual’s dentition is unique, no two sets of dentition are the same. This assumption was before the NAS and PCAST reports rebated that the uniqueness of dentition has not been proved.

There are a number of manual methods available for forensic odontology to use for the analysis of bite mark. However, BitePrint© software will be the main focus of this study as it is able to work with both 2D or 3D images. This software was chosen as the bite mark will be imprinted onto dental wax sheets, which will then be photographed and uploaded into the software for analysis. Furthermore, this software is able to provide information of the dental parameter such as rotation, distance to the arch from the centre of the circumference, eccentricity, and intercanine distance. This information is of significant value in identifying the dentition responsible for the mark. However, the validation of this software has not yet been reported and there has only been one study done in the investigation of the application of BitePrint© to the identification of dentition, this literature review will explore the possibility of it so that it can become another tool for the forensic odontology to use.

Item Type: Thesis (Masters by Research)
Murdoch Affiliation(s): School of Veterinary and Life Sciences
United Nations SDGs: Goal 16: Peace, Justice and Strong Institutions
Supervisor(s): Speers, James and Oatley, Giles
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