Using Stochastic Modeling for Texture Generation

Shinichiro Haruyama, Brian A. Barsky

研究成果: Article査読

38 被引用数 (Scopus)


Blinn2produced wrinkled and bumpy textures by perturbing the direction of the surface normal vector, but his method required specific texture pattern data for perturbation. Noting that rough textures have inherently random structures, we have developed a new computer graphics method that uses stochastic modeling to generate highly realistic random textures. Stochastic modeling has been used in computer graphics by Fournier, Fussell, and Car-penter3to generate stochastic curves and surfaces. We use a similar technique except that we apply the stochastic function to the normal vectors instead of the surface position. We also extend the fractional Brownian motion (fBm) form of stochastic modeling by allowing different values of the self-similarity parameter h on different recursion levels. The self-similarity parameter determines how fast a stochastic factor decreases as the recursion level becomes deeper. If h is zero, then the fBm parameter is the same for all recursion levels. A large h creates a very smooth texture and a small h makes a very rough texture; this means that h can control the spatial frequency distribution. By using different self-similarity parameters for different recursion levels, we can adjust the roughness in more detail and even control the size of the wrinkles easily. Futhermore, we can control the height of the bumps in the texture by adjusting the standard deviation σ.

ジャーナルIEEE Computer Graphics and Applications
出版ステータスPublished - 1984 3月

ASJC Scopus subject areas

  • ソフトウェア
  • コンピュータ グラフィックスおよびコンピュータ支援設計


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