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This dissertation provides four major contributions to the field of vision research. The first contribution is a general vision system model. The model, which blends biological as well as technological methods into a coherent approach to vision, will provide a basis for implementing vision systems. The second contribution of this dissertation is to demonstrate particular implementations of portions of the model. These implementations will include methods for using Gabor wavelets in edge detection, in preprocessing images for use as feature vectors in backpropagation neural networks, and as basis functions in a recognition/reconstruction network, as well as methods for integrating color into a vision system. The third major contribution is an investigation of attentional mechanisms using a two-part model with Gabor filters as a base attentional indicator. The second part of the model, the search mechanism, is only briefly studied. The final contribution is a description of an actual vision system for the analysis of VLSI circuits in terms of the general vision system model. This system provides a means of obtaining a logical circuit description from an actual physical circuit.