A Six-Stimulus Theory for Stochastic Texture

  • Authors:
  • Jan-Mark Geusebroek;Arnold W. M. Smeulders

  • Affiliations:
  • Intelligent Systems Lab Amsterdam, Informatics Institute, Faculty of Science, University of Amsterdam, Kruislaan, The Netherlands 403;Intelligent Systems Lab Amsterdam, Informatics Institute, Faculty of Science, University of Amsterdam, Kruislaan, The Netherlands 403

  • Venue:
  • International Journal of Computer Vision - Special Issue on Texture Analysis and Synthesis
  • Year:
  • 2005

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Abstract

We report a six-stimulus basis for stochastic texture perception. Fragmentation of the scene by a chaotic process causes the spatial scene statistics to conform to a Weibull-distribution. The parameters of the Weibull distribution characterize the spatial structure of uniform stochastic textures of many different origins completely. In this paper, we report the perceptual significance of the Weibull parameters. We demonstrate the parameters to be sensitive to orthogonal variations in the imaging conditions, specifically to the illumination conditions, camera magnification and resolving power, and the texture orientation. Apparently, the Weibull parameters form a six-stimulus basis for stochastic texture description. The results indicate that texture perception can be approached like the experimental science of colorimetry.