The Korean Journal of Applied Statistics (응용통계연구)

The Korean Statistical Society (한국통계학회)
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Efficient Edge Detection in Noisy Images using Robust Rank-Order Test

잡음영상에서 로버스트 순위-순서 검정을 이용한 효과적인 에지검출

  • Lim, Dong-Hoon (Department of Information Statistics and RINS, RICIC, Gyeongsang National University)
  • 임동훈 (경상대학교 정보통계학과)
  • Published : 2007.03.31
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Abstract

Edge detection has been widely used in computer vision and image processing. We describe a new edge detector based on the robust rank-order test which is a useful alternative to Wilcoxon test. Our method is based on detecting pixel intensity changes between two neighborhoods with a $r{\times}r$ window using an edge-height model to perform effectively on noisy images. Some experiments of our robust rank-order detector with several existing edge detectors are carried out on both synthetic images and real images with and without noise.

에지검출은 컴퓨터비전과 영상처리 시스템에서 널리 사용되는 단계이다. 본 논문에서는 잡음영상에서 효율적인 에지검출을 위해 이표본 위치 문제에서 월콕슨 검정의 대안인 로버스트 순위-순서 검정에 기초한 새로운 검출법을 제안하였다. 제안된 방법은 $\delta$-에지모형하에서 $5\times5$ 윈도우의 부분 픽셀만으로 구성된 근방영역 간에 통계적으로 유의한 차이가 있는지를 조사하였다. 제안된 에지 검출법의 성능을 평가하기 위해 실제영상과 인조영상을 가지고 영상실험을 통하여 얻은 에지맵과 객관적인 척도하에서 양적으로 비교 분석하였다.

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References

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