Robust ellipse detection via duality principle with a false determination control
In this paper, we propose a novel ellipse detection approach that eliminates false detection-based parameter space decomposition, principal of symmetric tangents, and a novel geometric constraint utilizing properties of tangents of ellipses. The principle of symmetric tangents provides better comput...
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sg-ntu-dr.10356-1404502020-05-29T04:06:40Z Robust ellipse detection via duality principle with a false determination control Dong, Huixu Chen, I-Ming Prasad, Dilip Kumar School of Computer Science and Engineering Proceedings of 2nd International Conference on Computer Vision & Image Processing (CVIP 2017) Robotics Research Centre Engineering::Computer science and engineering Ellipse Detection Principle of Geometric Duality In this paper, we propose a novel ellipse detection approach that eliminates false detection-based parameter space decomposition, principal of symmetric tangents, and a novel geometric constraint utilizing properties of tangents of ellipses. The principle of symmetric tangents provides better computational efficiency through confirmation of the ellipse center in the decomposed parameter space. The geometric constraint is used for alleviating the false detection probability. The experimental results confirm that the approach detects ellipse with an excellent accuracy at a high speed. 2020-05-29T04:06:39Z 2020-05-29T04:06:39Z 2018 Conference Paper Dong, H., Chen, I.-M., & Prasad, D. K. (2018). Robust ellipse detection via duality principle with a false determination control. Proceedings of 2nd International Conference on Computer Vision & Image Processing, 2, 223-234. doi:10.1007/978-981-10-7898-9_18 9789811078972 https://hdl.handle.net/10356/140450 10.1007/978-981-10-7898-9_18 2-s2.0-85047947325 2 223 234 en © 2018 Springer Nature Singapore Pte Ltd. All rights reserved. |
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Engineering::Computer science and engineering Ellipse Detection Principle of Geometric Duality |
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Engineering::Computer science and engineering Ellipse Detection Principle of Geometric Duality Dong, Huixu Chen, I-Ming Prasad, Dilip Kumar Robust ellipse detection via duality principle with a false determination control |
description |
In this paper, we propose a novel ellipse detection approach that eliminates false detection-based parameter space decomposition, principal of symmetric tangents, and a novel geometric constraint utilizing properties of tangents of ellipses. The principle of symmetric tangents provides better computational efficiency through confirmation of the ellipse center in the decomposed parameter space. The geometric constraint is used for alleviating the false detection probability. The experimental results confirm that the approach detects ellipse with an excellent accuracy at a high speed. |
author2 |
School of Computer Science and Engineering |
author_facet |
School of Computer Science and Engineering Dong, Huixu Chen, I-Ming Prasad, Dilip Kumar |
format |
Conference or Workshop Item |
author |
Dong, Huixu Chen, I-Ming Prasad, Dilip Kumar |
author_sort |
Dong, Huixu |
title |
Robust ellipse detection via duality principle with a false determination control |
title_short |
Robust ellipse detection via duality principle with a false determination control |
title_full |
Robust ellipse detection via duality principle with a false determination control |
title_fullStr |
Robust ellipse detection via duality principle with a false determination control |
title_full_unstemmed |
Robust ellipse detection via duality principle with a false determination control |
title_sort |
robust ellipse detection via duality principle with a false determination control |
publishDate |
2020 |
url |
https://hdl.handle.net/10356/140450 |
_version_ |
1681056400503996416 |