抄録
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.
| 元の言語 | English |
|---|---|
| ページ（範囲） | 611-623 |
| ページ数 | 13 |
| ジャーナル | IEICE Transactions on Information and Systems |
| 巻 | E93-D |
| 発行部数 | 3 |
| DOI | |
| 出版物ステータス | Published - 2010 |
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ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Software
- Artificial Intelligence
- Hardware and Architecture
- Computer Vision and Pattern Recognition
これを引用
Elliptical object detection by a modified ransac with sampling constraint from boundary Curves' clustering. / Xie, Yingdi; Ohya, Jun.
：: IEICE Transactions on Information and Systems, 巻 E93-D, 番号 3, 2010, p. 611-623.研究成果: Article
}
TY - JOUR
T1 - Elliptical object detection by a modified ransac with sampling constraint from boundary Curves' clustering
AU - Xie, Yingdi
AU - Ohya, Jun
PY - 2010
Y1 - 2010
N2 - 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.
AB - 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.
KW - A modified RANSAC
KW - Ellipse detection
UR - http://www.scopus.com/inward/record.url?scp=77950193677&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77950193677&partnerID=8YFLogxK
U2 - 10.1587/transinf.E93.D.611
DO - 10.1587/transinf.E93.D.611
M3 - Article
AN - SCOPUS:77950193677
VL - E93-D
SP - 611
EP - 623
JO - IEICE Transactions on Information and Systems
JF - IEICE Transactions on Information and Systems
SN - 0916-8532
IS - 3
ER -