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    Modelling wear patterns on footwear outsoles

    Francis, Xavier S.

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    MComp_2019_Soonu Xavier Francis_1487947_Final Research.pdf (18.15Mb)
    Date
    2019
    Citation:
    Francis, X. S. (2019). Modelling wear patterns on footwear outsoles (Unpublished document submitted in partial fulfilment of the requirements for the degree of Master of Computing). Unitec Institute of Technology, Auckland, New Zealand. Retrieved from https://hdl.handle.net/10652/4632
    Permanent link to Research Bank record:
    https://hdl.handle.net/10652/4632
    Abstract
    ABSTRACT: The outsoles of footwear develop nicks, cuts, and tears via repeated exposure to the abrasive forces that occur between the outsole and the ground. These abrasions result in the formation of characteristics unique to the outsole and the individual wearing them; additionally resulting in the degradation of the outsole design imprinted by the manufacturer. The combination of these characteristics allow the forensic scientist to uniquely identify the individual to whom it belongs. Quite often a period of time can elapse between the discovery of a shoeprint at the crime scene and the identification of a suspect. In these instances, the forensic scientist must rely on their training and expertise—developed through years of experience and study—to determine if the crime scene shoeprint matches the out-sole of the suspect’s shoe. This work introduces a computational framework capable of modelling wear patterns on the out-soles of footwear. This model is able to predict the evolution of the wear pattern after an arbitrary time period given in weeks. We introduce an additional model capable of reconstructing the outsole back to its original state on a given week. This framework—built on convolutional neural networks—provides an objective point of reference for forensic scientists in their evaluation of outsole wear patterns.
    Keywords:
    forensic podiatry, outsoles, footwear outsoles, soles, identification of criminals, crime suspects, shoeprints, computational forensics, modelling
    ANZSRC Field of Research:
    080108 Neural, Evolutionary and Fuzzy Computation, 1602 Criminology
    Degree:
    Master of Computing
    Supervisors:
    Sharifzadeh, Hamid; Newton, Angus; Baghaei, Nilufar
    ORCID Author Profiles
    • https://orcid.org/0000-0001-9793-9310
    Rights:
    This digital work is protected by copyright. It may be consulted by you, provided you comply with the provisions of the Act and the following conditions of use: Any use you make of these documents or images must be for research or private study purposes only, and you may not make them available to any other person. You will recognise the author's and publishers rights and give due acknowledgement where appropriate.
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    • Computing Dissertations and Theses [84]

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