Colin Ware
Abstract
Results from vision research are applied to the synthesis of visual texture for the purposes of information display. The literature surveyed suggests that the human visual system processes spatial information by means of parallel arrays of neurons that can be modeled by Gabor functions. Based on the Gabor model, it is argued that the fundamental dimensions of texture for human perception are orientation, size (1/frequency), and contrast. It is shown that there are a number of trade-offs in the density with which information can be displayed using texture. Two of these are (1) a trade-off between the size of the texture elements and the precision with which the location can be specified, and (2) the precision with which texture orientation can be specified and the precision with which texture size can be specified. Two algorithms for generating texture are included.
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Index Terms
Using visual texture for information display
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Reviews
Mircea Raducu Stan
Results in neurological vision research that suggest that human vision “processes spatial information by means of parallel arrays of neurons that can be modeled by Gabor functions” have led the authors to propose a method of generating texture for computer information display based on Gabor function “textons” (graphical texture primitives) characterized by orientation, size, and contrast (OSC texture space). A Gabor function is the product of a Gaussian envelope with a sinusoidal grating. A review of the mathematical results in vision research that support the use of Gabor textons as optimal stimuli for neural Gabor detectors is followed by discussions of space-frequency duality and an uncertainty principle of using texture for information display in which there are tradeoffs between texton size (1/spatial frequency) and precision in the space domain or texture orientation. Two texture synthesis algorithms are described as practical applications of the OSC model. The first algorithm uses Gabor textons with a modified Poisson random sampling of the data plane for texton placement. The second algorithm departs from the Gabor model and uses simple geometric shapes as textons. Although this research paper studies only the “spatial-frequency analysis” texture theory, it also cites the texture theory based on “probability and correlations” between neighboring textons as well as many other research works in perception, vision research, and computer graphics.
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