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Related Experiment Video

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Textures vs Non-Textures: A Simple Computational Method for Classifying Perceived 'Texturality' in Natural Images.

Fumiya Kurosawa1, Taiki Orima2, Kosuke Okada2

  • 1Department of Integrated Sciences, The University of Tokyo, Meguro-ku, Japan.

I-Perception
|December 8, 2021
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Summary

Human visual perception of textures is objectively measurable. This study links image texturality to specific statistical properties, enabling accurate discrimination of perceived textures.

Keywords:
natural image statisticsspatial visionsurfaces/materialstexture

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Area of Science:

  • Visual Perception
  • Computational Neuroscience
  • Image Processing

Background:

  • The human visual system efficiently processes scenes and surfaces using statistical representations of image textures.
  • The definition and objective identification of 'textures' in natural images have remained largely subjective.
  • Understanding the empirical basis of texture perception is crucial for visual system research.

Purpose of the Study:

  • To empirically investigate the conditions under which natural images are perceived as textures.
  • To establish an objective, quantitative link between image statistics and perceived texturality.
  • To develop a reliable method for determining if an image region is processed as a texture by the visual system.

Main Methods:

  • Correlation analysis between perceived texturality and image similarity to synthesized images using the Portilla-Simoncelli (PS) model.
  • Statistical analysis of image properties, focusing on specific PS statistics.
  • Development and validation of a discriminant model using image statistics to classify perceived textures.

Main Results:

  • Perceived texturality strongly correlates with the similarity between original images and their PS synthesized counterparts.
  • Both perceived texturality and similarity judgments are highly correlated with specific PS image statistics.
  • A discriminant model achieved over 90% accuracy in discriminating images perceived as textures.

Conclusions:

  • Image texturality can be objectively quantified and is linked to specific statistical image properties.
  • The Portilla-Simoncelli (PS) model and its associated statistics provide a basis for understanding texture perception.
  • This research offers a method to determine if image regions are statistically represented by the human visual system.