Ellipse detection based on RANSAC algorithm

RANSAC 알고리듬을 적용한 타원 검출

  • Received : 2012.12.13
  • Accepted : 2013.02.01
  • Published : 2013.01.30

Abstract

It plays an important role to detect the shape of an ellipse in many application areas of image processing. But it is very difficult to detect the ellipse in the real image because the noise was involved in the image, other objects obscured the ellipse or the ellipses were overlap with each other. In this paper, we extract the boundary (edge) to detect ellipse in the image and perform the grouping process in order to reduce amount of information. As a result, the speed of the ellipse detection was improved. Also in order to the ellipse detection, we selected the five ellipse parameters at random And then to select the optimal parameters of the ellipse, the linear least-squares approximation is applied. To verify the ellipse detection, RANSAC algorithm is applied. After the algorithm proposed in this study was implemented, the results applied to the real images showed an aocuracy of 75% and speed was very fast to compared with other researches. It mean that the proposed algorithm was valuable to detect the ellipses in the image.

영상처리로 물체를 검출 하는 경우, 타원 형태를 검출 하는 것은 많은 응용 분야에서 중요한 역할을 한다. 실제 영상에서 타원은 영상에 포함된 노이즈나 다른 물체에 가려 보이지 않거나 교차되어 타원 검출이 용이 하지 않다. 이에 본 논문에서는 영상에서 타원을 검출 하기 위하여 경계(edge)를 추출하고, 이미지 정보량을 줄이기 위하여 그룹화 과정을 수행하여 타원 검출의 속도를 향상시켰다. 또한 타원 검출을 위해 5 개의 타원 변수를 랜덤으로 선택한 후 최적의 타원 파라미터 선택을 위해 선형 최소자승 근사법을 적용하였다. 검출된 타원들을 검증하기 위하여 RANSAC 알고리즘을 적용하였다. 본 연구에서 제안한 알고리듬을 구현하여 실제 영상에 적용한 결과 75%의 정확도를 나타내었고, 타 연구와 비교 결과 타원검출 속도 면에서 탁월함을 확인하였다. 이러한 결과는 본 연구에서 제안한 알고리듬이 영상 내 타원을 검출 하기 위한 유효한 방법임을 확인 할 수 있었다.

Keywords

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