Predicting visual similarity between colour palettes

Jie Yang, Yun Chen*, Stephen Westland, Kaida Xiao

*此作品的通讯作者

科研成果: 期刊稿件文章同行评审

20 引用 (Scopus)

摘要

This work is concerned with the prediction of visual colour difference between pairs of palettes. In this study, the palettes contained five colours arranged in a horizontal row. A total of 95 pairs of palettes were rated for visual difference by 20 participants. The colour difference between the palettes was predicted using two algorithms, each based on one of six colour-difference formulae. The best performance (r2 = 0.86 and STRESS = 16.9) was obtained using the minimum colour-difference algorithm (MICDM) using the CIEDE2000 equation with a lightness weighing of 2. There was some evidence that the order (or arrangement) of the colours in the palettes was a factor affecting the visual colour differences although the MICDM algorithm does not take order into account. Application of this algorithm is intended for digital design workflows where colour palettes are generated automatically using machine learning and for comparing palettes obtained from psychophysical studies to explore, for example, the effect of culture, age, or gender on colour associations.

源语言英语
页(从-至)401-408
页数8
期刊Color Research and Application
45
3
DOI
出版状态已出版 - 1 6月 2020
已对外发布

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