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Investigating human color harmony preferences using unsuper-vised machine learning

机译:使用无监督机器学习研究人的色彩和谐偏好

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Color harmony patterns are relationships between coexisting colors where human psycho-perceptual visual pleasantness is the judging criterion. They play pivotal role in visualization, digital imaging and computer graphics. As a reference we assumed Itten model where harmony is expressed in terms of hue. The paper demonstrate investigation on color harmony patterns using clustering techniques. Our source data was Adobe Kuler database consisting of hundreds of thousands of color palettes prepared for creative purposes. For the color palettes dissimilarity measurement we propose to use Jaccard distance additionally treating colors as the elements of a fuzzy set. Then, in the next step, separate colors are grouped within each group of palettes to specify each scheme of relations. The results are schemes of relationships between color within palettes.
机译:色彩和谐模式是人类心理感知视觉愉悦感的判断标准,是两种色彩之间的关系。它们在可视化,数字成像和计算机图形学中起着关键作用。作为参考,我们假设使用Itten模型,其中色调以色调表示。本文演示了使用聚类技术对色彩和谐模式的研究。我们的源数据是Adobe Kuler数据库,其中包含成千上万个用于创意目的的调色板。对于调色板的相异性测量,我们建议使用Jaccard距离,另外将颜色视为模糊集的元素。然后,在下一步中,将单独的颜色分组在每组调色板中,以指定每种关系方案。结果是调色板内颜色之间关系的方案。

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