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Matching Of Feature Points using Dynamic Programming

동적 프로그래밍을 이용한 특징점 정합

  • 김동근 (천안공업대학 컴퓨터과)
  • Published : 2003.02.01

Abstract

In this paper we propose an algorithm which matches the corresponding feature points between the reference image and the search image. We use Harris's corner detector to find the feature points in both image. For each feature point in the reference image, we can extract the candidate matching points as feature points in the starch image which the normalized correlation coefficient goes greater than a threshold. Finally we determine a corresponding feature points among candidate points by using dynamic programming. In experiments we show results that match feature points in synthetic image and real image.

본 논문에서는 기준영상과 탐색영상 사이의 대응되는 특징 점을 정합 하는 알고리즘을 제안한다. 두 영상에서 특징 점을 찾기 위하여 Harris의 코너 점 검출기를 사용하였다. 기준영상의 각 특징 점에 대해, 정규상관계수가 임계치 이상인 탐색영상의 특징 점들로 후보 정합 점을 구한다. 최종적으로 동적 프로그래밍을 사용하여 후보 정합 점들 중에서 대응되는 특징 점을 구한다. 실험으로 인위적인 영상과 실제 영상에서 특징 점을 정합 하는 결과를 보였다.

Keywords

References

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