Non-contact, non-destructive approaches to detect and analyse artefacts recovered from crime scenes

Abstract

One of the most important aspects of crime scene investigation is the ability
to create an accurate reconstruction of the environment and the events that took
place leading up to the crime being committed. Because crime scenes are unstable
environments, time is of the essence. Conventional methods of detecting and
recovering evidence from crime scenes involve the use of chemicals and different
wavelengths of light in tandem with digital photography. However, these methods
are destructive or provide false positives. Alternative methods have been developed
or adopted from other areas of science, and in recent years, non-contact, nondestructive technologies have been employed in forensic applications. These
technologies have been used to capture entire scenes, traffic collisions, blood
pattern analysis, footwear and tyre impressions, and even fingerprint ridge detail.
The overall aim of this thesis is to undertake a series of proof-of-concept studies to
investigate how the use of non-contact, non-destructive technologies can be used
effectively to capture data from crime scenes to aid crime scene investigators in
their investigations. A structured light scanner (HP 3D Scan) was used to collect the
fingerprints from volunteers and the resulting 3D models converted to 2D images
and analysed in an automated fingerprint identification software. The same
structured light scanner was used to capture the impressions left behind on insoles
recovered from shoes, and measurements were compared against two other
methods of data capture. The hyperspectral camera (SpecIM IQ) was used to detect
and analyse bloodstained footwear marks on various types of substrates. The
results indicated that 3D fingerprints are still not compatible for fingerprint databases
but show promise, that 3D insoles offer a more reliable representation of an
impression, and that using a hyperspectral camera reveals more shoeprint detail
than conventional digital photography. The resultant data has helped to answer and
achieve the aims of this thesis. and even streamlined the search process performed
by Crime Scene Investigators. This work has highlighted the potential of digital noncontact, non-destructive methods to the application of crime scene science and
underlines the exciting future of this field.

Date of Award	2023
Original language	English
Awarding Institution	Teesside University
Supervisor	Timothy Thompson (Supervisor) & Meezanul Islam (Supervisor)