The KIPS Transactions:PartB (정보처리학회논문지B)

Korea Information Processing Society (한국정보처리학회)
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Shadow Detection Using Linearity of Shadow Brightness from a Single Natural Image

단일 자연영상에서 그림자 밝기의 선형성을 이용한 그림자 검출

  • 황동국 (충북대학교 컴퓨터공학과) ;
  • 박종천 (충북대학교 컴퓨터공학과) ;
  • 전병민 (충북대학교 컴퓨터공학과)
  • Published : 2008.12.31
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Abstract

This paper proposes a novel approach to shadow detection from a single natural image regardless of orientation and type of light sources. This approach is based on the assumption that shadow brightness changes linearly, and the axiom that a region cast shadow on is darker than that not having shadow under the same environment. Firstly, candidates for shadow are extracted by preprocessing. Then, they are quantized to replace the similar values with a representative value because of the more quantization steps of a pixel brightness, the higher linear independency among the neighboring pixels. Finally, shadows are detected according to linear independency of shadow brightness based on the assumption. The experimental results showed the proposed approach can robustly detect umbra as well as self-shadow and penumbra cast on a single-colored background.

본 논문은 그림자의 기하학 정보와 광원의 종류 및 방위에 관계없이 그림자 밝기가 점진적으로 변하거나 변화가 없다는 가정과 그림자는 어둡다는 공리를 기반으로 임의의 복잡한 자연 영상에서 그림자를 검출하는 기법을 제안한다. 먼저, 전처리를 통하여 그림자 후보영상을 검출한다. 다음으로, 인접화소들 사이의 선형독립성을 낮추기 위하여 유사 밝기를 대표 밝기로 표현하는 균일 양자화를 수행한다. 마지막으로, 그림자 밝기의 선형적 변화 특성을 이용하여 선형독립성이 낮은 그림자를 검출한다. 임의의 단일 자연영상의 실험에서, 제안한 알고리즘은 본영과 단색 배경을 갖는 반영 및 셀프그림자의 검출에 강건함을 보였다.

Keywords

References

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