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Employing a structuration-derived theoretical approach, this thesis provides a detailed phenomenological account of the everyday life of surveillance systems as conveyed in the narratives and practices of particular sets of surveillance workers. Using an ethnographic approach, and focusing critical attention on how Closed Circuit Television (CCTV) operators ethnomethodologically order, experience and make sense of the physical spaces they inhabit and the mediated realities (simulated spaces) into which they are intimately thrust as an ‘absent presence’, the reader is taken deep within the cultural lifeworld of such settings and is introduced to their ontologically-defining interactional and emotional orders. By analysing the myriad of social relationalities in which the surveillance worker is continually entrenched, consideration is given to systemic formulation (i.e. how systems are interactively constructed as a result of subjective processes), systemic operation (i.e. how operators hermeneutically interpret, relate to, cope and interact with the various images and realities depicted) and systemic experience (i.e. how surveillance systems affect those tasked with their everyday control). Subjectivity is identified as being a crucial constitutive force in each process and a significant variable influencing social system dynamicism. Understanding contradictions and unintended consequences within surveillance practice as being an outcome of the interactional relations and struggles between agents and structures, this thesis shows the lifeworld to be the ‘lifeblood’ not only of social system operationalisation, maintenance and transformation, but also of social scientific analysis.

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Shoeprints are routinely left at crone scenes and are reported to be present more frequently than fingerprints. It has been reported that 35 percent of crime scenes present shoe marks that can be recovered and used as forensic evidence. During investigations, a scene of crime shoeprint can be matched against a database of known shoeprints in order to identify the brand and the model of the corresponding shoe. TIlls is known as shoeprint classification and is, currently, performed manually or using some semi-automatic systems. These current approaches are time consuming and are not very reliable. Thus, the development of automatic shoeprint classification methods would offer valuable assistance to forensic scientists. TIlls thesis addresses the task of automatic shoeprint classification and its related challenges. This includes the problem of classifying partial, noisy and/or blurred shoeprint images. The issues of invariance to geometric distortions, e.g. translations and rotations, as well as rapid classification are also considered. The thesis proposes a number of different ideas and methods for the automatic classification of distorted shoeprint images including the use of Fourier-Mellin transform, modified phase-only correlation and two-dimensional advanced correlation filters. It also investigates the use of multiple one-dimensional correlation filters and classifier combination techniques, such as algebraic rules, Decision Templates and Support Vector Machine based combiners. The experimental results suggest that the investigated correlation-based methods can offer high accuracies when classifying low quality shoeprint images while providing tolerance to geometric distortions.

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