Journal of KIISE:Computer Systems and Theory (한국정보과학회논문지:시스템및이론)

Korean Institute of Information Scientists and Engineers (한국정보과학회)
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Automatic Color Palette Extraction for Paintings Using Color Grouping and Clustering

색상 그룹핑과 클러스터링을 이용한 회화 작품의 자동 팔레트 추출

  • 이익기 (중앙대학교 컴퓨터공학부) ;
  • 이창하 (중앙대학교 컴퓨터공학부) ;
  • 박재화 (중앙대학교 컴퓨터공학부)
  • Published : 2008.08.15
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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.

화풍을 효과적이고 객관적으로 기술하는 한 방법으로 팔레트 추출에 대한 수학적 모델을 제시한다. 이 모델에서는 팔레트를 허용 오차 범위 내에서 회화 작품의 영상을 표현할 수 있는 주요 색상의 집합으로 정의하고 색상 그룹핑과 주요 색상 추출의 두 단계를 거처 팔레트 색상을 추출한다. 색상 그룹핑은 주어진 회화에 대해 적응적으로 색의 분해능을 조절하여 각 회화 작품을 이루는 기초 색상을 추출하며 다음 주요 색상 추출 단계에서 이것과 이것이 차지하는 영역에 대한 정보를 바탕으로 K-Means 클러스터링 알고리즘을 적용하여 팔레트를 얻는다. 실험을 통해 유명 화가의 작품을 대상으로 RGB와 CIE LAB 색상 모델을 사용하여 추출한 팔레트를 3차원 색 공간에 표시하였다. 팔레트 색상의 거리를 사용한 화가 분류 실험과 실사 영상의 색채 변환 실험 통해 이 방법이 화풍 분석과 그래픽 분야에 적용될 수 있음을 확인하였다.

Keywords

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