Efficient detection of ellipses from an image by a guided modified ransac

Yingdi Xie*, Jun Ohya


研究成果: Conference contribution

6 被引用数 (Scopus)


In this paper, we propose a novel ellipse detection method which is based on a modified RANSAC, with automatic sampling guidance from the edge orientation difference curve. Hough Transform family is one of the most popular and methods for shape detection, but the Standard Hough Transform loses its computation efficiency if the dimension of the parameter space gets high. Randomized Hough Transform, an improved version of Standard Hough Transform has difficulty in detecting shapes from complicated, cluttered scenes because of its random sampling process. As a pre-process for random selection of five pixels to be used to build the ellipse's equation, we propose a two-step algorithm: (1) region segmentation and contour detection by mean shift algorithm (2) contour splitting based on the edge orientation difference curve obtained from the contour of each region. In each contour segment obtained by step (2), 5 pixels are randomly selected and the modified RANSAC is applied to the 5 pixels so that an accurate ellipse model is obtained. Experimental result show that the proposed method can achieve high accuracies and low computation cost in detecting multiple ellipses from an image.

ホスト出版物のタイトルProceedings of SPIE-IS and T Electronic Imaging - Image Processing
ホスト出版物のサブタイトルAlgorithms and Systems VII
出版ステータスPublished - 2009 6月 15
イベントImage Processing: Algorithms and Systems VII - San Jose, CA, United States
継続期間: 2009 1月 192009 1月 22


名前Proceedings of SPIE - The International Society for Optical Engineering


ConferenceImage Processing: Algorithms and Systems VII
国/地域United States
CitySan Jose, CA

ASJC Scopus subject areas

  • 電子材料、光学材料、および磁性材料
  • 凝縮系物理学
  • コンピュータ サイエンスの応用
  • 応用数学
  • 電子工学および電気工学


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