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Proceedings Paper

Efficient detection of ellipses from an image by a guided modified RANSAC
Author(s): Yingdi Xie; Jun Ohya
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Paper Abstract

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.

Paper Details

Date Published: 11 February 2009
PDF: 14 pages
Proc. SPIE 7245, Image Processing: Algorithms and Systems VII, 72450W (11 February 2009); doi: 10.1117/12.805891
Show Author Affiliations
Yingdi Xie, Waseda Univ. (Japan)
Jun Ohya, Waseda Univ. (Japan)

Published in SPIE Proceedings Vol. 7245:
Image Processing: Algorithms and Systems VII
Nasser M. Nasrabadi; Syed A. Rizvi; Jaakko T. Astola; Karen O. Egiazarian, Editor(s)

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