Paper
8 October 1996 Genetic algorithms for texture model identification and synthesis
Cory J. Engebretson, Jennifer L. Davidson, Dan Ashlock
Author Affiliations +
Abstract
This paper presents research on texture modeling and regeneration. We view a texture as a large pattern created from regular repetitions of a small, basic texture element, or texel. Given a texture image, the problem was to find the 'best' texel for that data, regenerate the texture represented by that texel, and compare the original image and the regenerated one. The texel-finding problem was posed as an optimization procedure. We used a genetic algorithm to do the optimization. To regenerate the texture, we used a Metropolis-like algorithm. The textures regenerated from the texels found by the genetic algorithm were difficult to visually distinguish from the original data. Research efforts are continuing to improve the efficiency and accuracy of the method and to extend the method to different types of data.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Cory J. Engebretson, Jennifer L. Davidson, and Dan Ashlock "Genetic algorithms for texture model identification and synthesis", Proc. SPIE 2823, Statistical and Stochastic Methods for Image Processing, (8 October 1996); https://doi.org/10.1117/12.253457
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Cited by 1 scholarly publication.
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KEYWORDS
Genetic algorithms

Binary data

Optimization (mathematics)

Image processing

Image transmission

Legal

Stochastic processes

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