Journal of the Institute of Electronics Engineers of Korea SP (대한전자공학회논문지SP)

The Institute of Electronics and Information Engineers (대한전자공학회)
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Optimal Combination of Component Images for Segmentation of Color Codes

칼라 코드의 영역 분할을 위한 성분 영상들의 최적 조합

  • Published : 2005.01.01
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Abstract

Identifying color codes needs precise color information of their constituents, and is far from trivial because colors usually suffer severe distortions throughout the entire procedures from printing to acquiring image data. To accomplish accurate identification of colors, we need a reliable segmentation method to separate different color regions from each other, which would enable us to process the whole pixels in the region of a color statistically, instead of a subset of pixels in the region. Color image segmentation can be accomplished by performing edge detection on component image(s). In this paper, we separately detected edges on component images from RGB, HSI, and YIQ color models, and performed mathematical analyses and experiments to find out a pair of component images that provided the best edge image when combined. The best result was obtained by combining Y- and R-component edge images.

칼라 화소 성분들은 인쇄에서부터 획득하기까지의 전 과정에 거쳐 심하게 왜곡되기 때문에, 획득된 영상에서 정확한 칼라 정보를 필요로 하는 칼라 코트 식별 작업은 매우 어렵다. 정확한 칼라 식별을 달성하기 위해서는 서로 다른 칼라 영역들을 정화하게 분리해냄으로써 어떤 칼라 영역의 부분이 아닌 전체 화소들에 대한 통계적 처리를 가능하게 하는 영역 분할 기술이 필요하다. 칼라 영역 분한은 성분 영상(들)에 대한 경계선 검출을 수행하여 달성할 수 있다. 이 논문에서는 RGB, HSI, YIQ의 세 칼라 모델로부터의 성분 영상들에 대해 독립적으로 경계선을 검출하고, 결합에 의해 가장 완전한 경계선 영상을 제공하는 한쌍의 성분을 찾아내기 위한 수학적 분석과 실험을 수행하였다. 실험 결과, Y-와 R-성분 경계선 영상들을 결합했을 때 가장 좋은 결과를 얻을 수 있었다.

Keywords

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