This thesis presents a number of modifications to a blind aid, known as the video optophone, which enables a blind user to more readily interpret their local environment for enhanced mobility and navigation. Versions of this form of blind aid are generally both difficult to use and interpret, and are therefore inadequate for safe mobility. The reason for this severe problem lies in the complexity and excessive bandwidth of the optophonic output after the conversion from scene-to-sound. The work herein describes a number of modifications that can be applied to the current optophonic process to make more efficient use of the limited bandwidth provided by the auditory system when converting scene images to sound. Various image processing and stereo techniques have been employed to artificially emulate the human visual system through the use of depth maps that successfully fade out the quantity of relatively unimportant image features, whilst emphasising the more significant regions such as nearby obstacles. A series of experiments were designed to test these various modifications to the optophonic mapping by studying important factors of mobility and subject response whilst going about everyday life. The devised system, labelled DeLIA for the Detection, Location, Identification, and Avoidance (or Action) of obstacles, provided a means for gathering statistical data on users’ interpretation of the optophonic output. An analysis of this data demonstrated a significant improvement when using the stereo cartooning technique, developed as part of this work, over the more conventional plain image as an input to an optophonic mapping from scene-to-sound. Lastly, conclusions were drawn from the results, which indicated that the use of a stereo depth map as an input to a video optophone would improve its usefulness as an aid to general mobility. For the purposes of detecting and determining text or similar detail, either a plain unmodified image or some form of edge (depth) image were found to produce the best results

The formation of a plaque in one or both of the internal carotid arteries poses a serious threat to the lives of those in whom it occurs. This thesis describes a technique designed to detect level of occlusion and provide topological information about such plaques. In order to negate the cost of specialised hardware, only the sound produced by blood-flow around the occlusion is used; this raises problems that prevent the application of existing medical imaging techniques, however, these can be overcome by the application of a nonlinear technique that takes full advantage of the discrete nature of digital computers. Results indicate that both level of occlusion and presence or absence of various topological features can be determined in this way. Beginning with a review of existing work in medical-imaging and in more general but related techniques, the EPI process of Friden (2004) is identified as the strongest approach to a situation where it is desirable to work with both signal and noise yet avoid the computational cost and other pitfalls of established techniques. The remained of the thesis discusses attempts to automate the EPI process which, in the form given by Frieden (2004), requires a degree of human mathematical creative problem-solving. Initially, a numerical-methods inspired approach based on genetic algorithms was attempted but found to be both computationally costly and insufficiently true to the nature of the EPI equations. A second approach, based on the idea of creating a formal system allowing entropy, direction and logic to be manipulated together proved to lack certain key properties and require an amount of work beyond the scope of the project described in this thesis in order to be extended into a form that was usable for the EPI process. The approach upon which the imaging system described is ultimately built is based on an abstracted form of constraint-logic programming resulting in a cellular-automaton based model which is shown to produce distinct images for different sizes and topologies of plaque in a reliable and human-interpretable way.