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Title: Forensic investigation of static bare footprints sampled from three distinct races, white British, Chinese and Indians
Author: Jira, Paul
ISNI:       0000 0004 8502 6321
Awarding Body: Staffordshire University
Current Institution: Staffordshire University
Date of Award: 2019
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Bare footprints, marks or impressions found at crime scenes can potentially provide criminal investigators with intelligence relating to the stature, gait of a perpetrator or aid the reconstruction of a crime scene. Currently, little is known about the inter- and intra-variations in bare footprint morphologies or the prevalence of certain characteristics in bare footprints from distinct races. To understand such variability requires large datasets of bare footprints. One of the primary aims of this thesis was to develop a novel, inexpensive method to record control samples and use the method to generate large datasets of bare footprints. The reliability of this method was investigated, and the qualitative and quantitative results indicated that there was repeatability and comparability between the new method (lotion) and the industry standard existing methods, for example, the inkless shoeprint kit and fingerprint ink. Following the successful testing of the lotion method, the lotion was used to gather static control bare footprints from three distinct races, White British (n = 25); Chinese (n =25); and Indian (n = 25). The quantitative data consisting of the footprint dimensions were converted to ratios. In addition, the foot outline was converted to morphological landmarks and the data was analysed using principle component analysis (PCA) and model-based cluster analysis (MBCA) to investigate the relationships between the three races. The results showed that the data from the three races could be placed into their respective racial groups using the x and y morphometric landmark coordinates. The resulting bare footprints data generated during this project was subsequently used to establish a database in Microsoft Access Database (MAD) to allow the data to be stored and new data to be added in, for future research work.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available