Image archiving is important in various applications. In this work, we formulate the problem of compressing image archives as an optimization problem and present an efficient method for solving this problem. Our method is based on adapting SPIHT to image archiving where the total bit budget is distributed optimally across the images. We show experimentally that this method significantly outperforms its counter-part, namely, SPIHT with equal distribution of bit budget.

The purpose of this study was to investigate the effects of neighborhood and family influences on body image and dietary attitudes in a cohort of 10-and 11-year old children across the BMI spectrum. In this cross-sectional study, age-appropriate figure drawings, Dietary Restraint and Body Esteem Scales were administered to 554 boys and girls. Information on parent and neighborhood influences were gathered from participants’ parents and tested for association with child variables through multiple linear regression. This study indicates that parent modeling variables have an association with child body esteem and dietary restraint when BMI is controlled. Socioeconomic status was found to play a role, with high socioeconomic neighborhoods resulting in higher body esteem and dietary restraint. Geographic location had no influence over child variables. Overall, important influences were found between parent and socioeconomic status variables and body esteem and restraint.

This thesis describes the research carried out in overcoming the problems encountered during the development of an autonomous mobile robot (AMR) which uses a single television camera for navigation in environments with visible edges, such as corridors and hallways. The objective was to determine the minimal sensing and signal processing requirements for a real AMR that could achieve self-steering, navigation and obstacle avoidance in real unmodified environments. A goal was to design algorithms that could meet the objective while being able to run on a laptop personal computer (PC). This constraint confined the research to computationally efficient algorithms and memory management techniques. The methods by which the objective was successfully achieved are described. A number of noise reduction and feature extraction algorithms have been tested to determine their suitability in this type of environment, and where possible these have been modified to improve their performance. The current methods of locating lines of perspective and vanishing points in images are described, and a novel algorithm has been devised for this application which is more efficient in both its memory usage and execution time. A novel obstacle avoidance mechanism is described which is shown to provide the low level piloting capability necessary to deal with unexpected situations. The difficulties of using a single camera are described, and it is shown that a second camera is required in order to provide robust performance. A prototype AMR was built and used to demonstrate reliable navigation and obstacle avoidance in real time in real corridors. Test results indicate that the prototype could be developed into a competitively priced commercial service robot.

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Visual perception of images is closely related to the recognition of the different texture areas within an image. Identifying the boundaries of these regions is an important step in image analysis and image understanding. This thesis presents supervised and unsupervised methods which allow an efficient segmentation of the texture regions within multi-texture images. The features used by the methods are based on a measure of the fractal dimension of surfaces in several directions, which allows the transformation of the image into a set of feature images, however no direct measurement of the fractal dimension is made. Using this set of features, supervised and unsupervised, statistical processing schemes are presented which produce low classification error rates. Natural texture images are examined with particular application to the analysis of sonar images of the seabed. A number of processes based on fractal models for texture synthesis are also presented. These are used to produce realistic images of natural textures, again with particular reference to sonar images of the seabed, and which show the importance of phase and directionality in our perception of texture. A further extension is shown to give possible uses for image coding and object identification.

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