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Not All Color Categories Are Equally Stable: A Multilingual Free Color Naming Experiment

arXiv 2607.10465 ↗First posted 11 Jul 2026cs.CV cs.CLcited by 0

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Abstract (arXiv)

Color naming is an important part of human color perception. Its task is to allow people to describe continuous colors using discrete color categories. However, the boundaries between color categories are often unclear, and some colors may be perceived differently depending on their saturation and brightness. While certain color categories remain recognizable across a wide range of shades, others may be associated with different color names when their appearance changes. This study investigates the consistency of color naming for red, yellow, and green color categories using a free color-naming experiment. A set of 18 color samples was selected from the COLIBRI dataset to represent different shades of these colors. Participants (n = 92) were asked to freely assign color names to each sample in Kazakh, Russian, or English without being limited to predefined categories. The results show that color categories differ in their consistency. Green shades were consistently identified as green despite variations in appearance, whereas yellow shades received a wider variety of names, including gold- and brown-related descriptions. Red shades showed moderate naming consistency. Our findings suggest that some color categories occupy broader perceptual regions than others and may therefore be more robust to visual variations. The study results can be used to develop perceptually meaningful color models and color naming systems.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 5 of its 28 references that are in the map. First posted on arXiv 11 Jul 2026.

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References · 5

  1. 2021Can Language Models Encode Perceptual Structure Without Grounding? A Case Study in Colorcited by 119
  2. 2025COLIBRI Fuzzy Model: Color Linguistic-Based Representation and Interpretationcited by 6
  3. 2024Comparative Analysis Of Color Models For Human Perception And Visual Color Differencecited by 5
  4. 2025Color Models in Image Processing: A Review and Experimental Comparisoncited by 4
  5. 2026Toward a Universal Color Naming System: A Clustering-Based Approach using Multisource Datacited by 1

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