On colour categorization of nature

S. Yendrikhovskij
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Abstract

The following research elaborates on some of the 'semantic' and 'algorithmic' aspects of the categorization process for thc colour domain. The structure of colour categories is argued to resemble the structure of Ihe distribution of colours in the perceived world. This distribution can be represented as colour statistics in some perceptual and approximately uniform colour space (e.g., the CIELUV colour space). We propose that the process of colour categorization is determined by a trade-off between (1) accuracy in representation of perceived colours and (2) simplicity of the category system. Colour categorization can be represented through the grouping of colour statistics by clustering algorithms (e.g., K-means). These assumptions are analysed on the basis of colour statistics of 630 natural images in the CIELUV colour space.
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论自然的色彩分类
下面的研究详细阐述了颜色域分类过程的一些“语义”和“算法”方面。认为颜色范畴的结构类似于感知世界中颜色分布的结构。这种分布可以表示为一些感知和近似均匀的颜色空间(例如,CIELUV颜色空间)中的颜色统计。我们提出,颜色分类过程是由(1)感知颜色表示的准确性和(2)类别系统的简单性之间的权衡决定的。颜色分类可以通过聚类算法(如K-means)对颜色统计进行分组来表示。在对630幅自然图像的CIELUV色彩空间进行色彩统计的基础上,对这些假设进行了分析。
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