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Traditionally artistic color concepts play an important role in the analysis of artworks, and provide valuable domain knowledge to guide the analysis and accurate retrieval of paintings. This paper presents an automated approach to analyzing and representing artistic color concepts such as color temperature, color palette and color contrasts in paintings domain. The color concept definitions rely on the widely accepted color theory of Itten. Our approach starts with the extraction of homogeneous color/texture regions from paintings, and employs image processing and machine learning techniques to characterize regions in terms of artistic color concepts. We evaluate the proposed method using collection of 1,000 paintings, which exhibit vast variety of painting styles and artistic color concepts. Experiments show that our method performs well for a vast variety of both spatial and non-spatial artistic color concept queries.
Yelizaveta et al. (Mon,) studied this question.