Influence of Texture Structure on the Perception of Color Composition

Journal Article (2020)
Author(s)

Jing Wang (Bloomburg LP, New York)

Jana Zujovic (Google LLC)

June Choi (Accenture)

Basabdutta Chakraborty (Amway, Ada)

R Van Egmond (TU Delft - Human Technology Relations)

Huib De Ridder (TU Delft - Human Technology Relations)

Thrasyvoulos N. Pappas (Northwestern University)

Research Group
Human Technology Relations
Copyright
© 2020 Jing Wang, Jana Zujovic, June Choi, Basabdutta Chakraborty, R. van Egmond, H. de Ridder, Thrasyvoulos N. Pappas
DOI related publication
https://doi.org/10.2352/J.Percept.Imaging.2020.3.1.010401
More Info
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Publication Year
2020
Language
English
Copyright
© 2020 Jing Wang, Jana Zujovic, June Choi, Basabdutta Chakraborty, R. van Egmond, H. de Ridder, Thrasyvoulos N. Pappas
Research Group
Human Technology Relations
Issue number
1
Volume number
3
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Abstract

The authors explore the influence of the structure of a texture image on the perception of its color composition through a series of psychophysical studies. They estimate the color composition of a texture by extracting its dominant colors and the associated percentages. They then synthesize new textures with the same color composition but different geometric structural patterns. They conduct empirical studies in the form of two-alternative forced choice tests to determine the influence of two structural factors, pattern scale and shape, on the perceived amount of target color. The results of their studies indicate that (a) participants are able to consistently assess differences in color composition for textures of similar shape and scale, and (b) the perception of color composition is nonveridical. Pattern scale and shape have a strong influence on perceived color composition: the larger the scale, the higher the perceived amount of the target color, and the more elongated the shape, the lower the perceived amount of the target color. The authors also present a simple model that is consistent with the results of their empirical studies by accounting for the reduced visibility of the pixels near the color boundaries. In addition to a better understanding of human perception of color composition, their findings will contribute to the development of color texture similarity metrics.

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