Elliptical Object Detection by a Modified RANSAC with Sampling Constraint from Boundary Curves' Clustering
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概要
- 論文の詳細を見る
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 well-known conventional method.
- （社）電子情報通信学会の論文
- 2010-03-01
著者
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XIE Yingdi
Graduate School of Global Information and Telecommunication and Studies, Waseda University
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OHYA Jun
Graduate School of Global Information and Telecommunication and Studies, Waseda University
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Ohya Jun
Graduate School Of Grobal Information And Telecommunication Studies Waseda University
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Xie Yingdi
Graduate School Of Grobal Information And Telecommunication Studies Waseda University
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Xie Yingdi
Graduate School Of Global Information And Telecommunication And Studies Waseda University
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Ohya Jun
Graduate School Of Global Information And Telecommunication And Studies Waseda University
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