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Automatic Color Palette Extraction for Paintings Using Color Grouping and Clustering  

Lee, Ik-Ki (중앙대학교 컴퓨터공학부)
Lee, Chang-Ha (중앙대학교 컴퓨터공학부)
Park, Jae-Hwa (중앙대학교 컴퓨터공학부)
Publication Information
Journal of KIISE:Computer Systems and Theory / v.35, no.7, 2008 , pp. 340-353 More about this Journal
Abstract
A computational color palette extraction model is introduced to describe paint brush objectively and efficiently. In this model, a color palette is defined as a minimum set of colors in which a painting can be displayed within error allowance and extracted by the two step processing of color grouping and major color extraction. The color grouping controls the resolution of colors adaptively and produces a basic color set of given painting images. The final palette is obtained from the basic color set by applying weighted k-means clustering algorithm. The extracted palettes from several famous painters are displayed in a 3-D color space to show the distinctive palette styles using RGB and CIE LAB color models individually. And the two experiments of painter classification and color transform of photographic image has been done to check the performance of the proposed method. The results shows the possibility that the proposed palette model can be a computational color analysis metric to describe the paint brush, and can be a color transform tool for computer graphics.
Keywords
palette extraction; color grouping; color clustering; paint brush analysis;
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