Elliptical object detection by a modified ransac with sampling constraint from boundary Curves' clustering

Yingdi Xie, Jun Ohya

Research output: Contribution to journalArticle

5 Citations (Scopus)


This paper proposes a method for detecting ellipses from an image despite (1) multiple colors within the ellipses, (2) partially occluded ellipses' boundaries, (3) noisy, locally deformed boundaries of ellipses, (4) presence of multiple objects other than the ellipses in the image, and (5) combinations of (1) through (4). After boundary curves are obtained by edge detection, by utilizing the first-order difference curves of the edge orientation of each pixel in the boundary curves, a segment-reconnect method obtains boundary clusters. Then, a modified RANSAC detects ellipses by choosing five pixels randomly from the boundary clusters, where overlapped ellipses are merged. Experimental results using synthesized images and real images demonstrate the effectiveness of the proposed method together with comparison with the Randomized Hough Transform, a wellknown conventional method.

Original languageEnglish
Pages (from-to)611-623
Number of pages13
JournalIEICE Transactions on Information and Systems
Issue number3
Publication statusPublished - 2010 Jan 1



  • A modified RANSAC
  • Ellipse detection

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering
  • Artificial Intelligence

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