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Proceedings Paper

Genetic algorithms for texture model identification and synthesis
Author(s): Cory J. Engebretson; Jennifer L. Davidson; Dan Ashlock
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Paper 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.

Paper Details

Date Published: 8 October 1996
PDF: 12 pages
Proc. SPIE 2823, Statistical and Stochastic Methods for Image Processing, (8 October 1996); doi: 10.1117/12.253457
Show Author Affiliations
Cory J. Engebretson, Iowa State Univ. (United States)
Jennifer L. Davidson, Iowa State Univ. (United States)
Dan Ashlock, Iowa State Univ. (United States)


Published in SPIE Proceedings Vol. 2823:
Statistical and Stochastic Methods for Image Processing
Edward R. Dougherty; Francoise J. Preteux; Jennifer L. Davidson, Editor(s)

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