Color terms are used to express light spectrum characteristics captured by human vision, and color naming across languages partition color spaces differently. Such partition differences have been surveyed through several empirical experiments that employ Munsell color chips. We propose a novel visualization method for color terms based on thousands of images collected from query results provided by an image search engines such as Google. A series of experiments was conducted using eight basic color terms in seven languages. Pixel values in the images are counted to form color histograms according to the color pallet used in the world color survey. The visualization results can be summarized as follows: (1) Japanese and Korean color terms have wider distributions in the color space than terms in other languages do and (2) color visualizations for color terms pink and brown are affected by their links to proper nouns.
['Nobuyuki Umezu', 'Eriho Takahashi']
Visualizing color term differences based on images from the web