TGGLinesPlus: A robust topological graph-guided computer vision algorithm for line detection from images ...
Line detection is a classic and essential problem in image processing, computer vision and machine intelligence. Line detection has many important applications, including image vectorization (e.g., document recognition and art design), indoor mapping, and important societal challenges (e.g., sea ice...
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Online Access: | https://dx.doi.org/10.48550/arxiv.2403.18038 https://arxiv.org/abs/2403.18038 |
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ftdatacite:10.48550/arxiv.2403.18038 2024-04-28T08:37:53+00:00 TGGLinesPlus: A robust topological graph-guided computer vision algorithm for line detection from images ... Yang, Liping Driscol, Joshua Gong, Ming Wang, Shujie Potts, Catherine G. 2024 https://dx.doi.org/10.48550/arxiv.2403.18038 https://arxiv.org/abs/2403.18038 unknown arXiv arXiv.org perpetual, non-exclusive license http://arxiv.org/licenses/nonexclusive-distrib/1.0/ Computer Vision and Pattern Recognition cs.CV FOS Computer and information sciences article Article Preprint CreativeWork 2024 ftdatacite https://doi.org/10.48550/arxiv.2403.18038 2024-04-02T12:49:47Z Line detection is a classic and essential problem in image processing, computer vision and machine intelligence. Line detection has many important applications, including image vectorization (e.g., document recognition and art design), indoor mapping, and important societal challenges (e.g., sea ice fracture line extraction from satellite imagery). Many line detection algorithms and methods have been developed, but robust and intuitive methods are still lacking. In this paper, we proposed and implemented a topological graph-guided algorithm, named TGGLinesPlus, for line detection. Our experiments on images from a wide range of domains have demonstrated the flexibility of our TGGLinesPlus algorithm. We also benchmarked our algorithm with five classic and state-of-the-art line detection methods and the results demonstrate the robustness of TGGLinesPlus. We hope our open-source implementation of TGGLinesPlus will inspire and pave the way for many applications where spatial science matters. ... : Our TGGLinesPlus Python implementation is open source. 27 pages, 8 figures and 4 tables ... Article in Journal/Newspaper Sea ice DataCite Metadata Store (German National Library of Science and Technology) |
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DataCite Metadata Store (German National Library of Science and Technology) |
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unknown |
topic |
Computer Vision and Pattern Recognition cs.CV FOS Computer and information sciences |
spellingShingle |
Computer Vision and Pattern Recognition cs.CV FOS Computer and information sciences Yang, Liping Driscol, Joshua Gong, Ming Wang, Shujie Potts, Catherine G. TGGLinesPlus: A robust topological graph-guided computer vision algorithm for line detection from images ... |
topic_facet |
Computer Vision and Pattern Recognition cs.CV FOS Computer and information sciences |
description |
Line detection is a classic and essential problem in image processing, computer vision and machine intelligence. Line detection has many important applications, including image vectorization (e.g., document recognition and art design), indoor mapping, and important societal challenges (e.g., sea ice fracture line extraction from satellite imagery). Many line detection algorithms and methods have been developed, but robust and intuitive methods are still lacking. In this paper, we proposed and implemented a topological graph-guided algorithm, named TGGLinesPlus, for line detection. Our experiments on images from a wide range of domains have demonstrated the flexibility of our TGGLinesPlus algorithm. We also benchmarked our algorithm with five classic and state-of-the-art line detection methods and the results demonstrate the robustness of TGGLinesPlus. We hope our open-source implementation of TGGLinesPlus will inspire and pave the way for many applications where spatial science matters. ... : Our TGGLinesPlus Python implementation is open source. 27 pages, 8 figures and 4 tables ... |
format |
Article in Journal/Newspaper |
author |
Yang, Liping Driscol, Joshua Gong, Ming Wang, Shujie Potts, Catherine G. |
author_facet |
Yang, Liping Driscol, Joshua Gong, Ming Wang, Shujie Potts, Catherine G. |
author_sort |
Yang, Liping |
title |
TGGLinesPlus: A robust topological graph-guided computer vision algorithm for line detection from images ... |
title_short |
TGGLinesPlus: A robust topological graph-guided computer vision algorithm for line detection from images ... |
title_full |
TGGLinesPlus: A robust topological graph-guided computer vision algorithm for line detection from images ... |
title_fullStr |
TGGLinesPlus: A robust topological graph-guided computer vision algorithm for line detection from images ... |
title_full_unstemmed |
TGGLinesPlus: A robust topological graph-guided computer vision algorithm for line detection from images ... |
title_sort |
tgglinesplus: a robust topological graph-guided computer vision algorithm for line detection from images ... |
publisher |
arXiv |
publishDate |
2024 |
url |
https://dx.doi.org/10.48550/arxiv.2403.18038 https://arxiv.org/abs/2403.18038 |
genre |
Sea ice |
genre_facet |
Sea ice |
op_rights |
arXiv.org perpetual, non-exclusive license http://arxiv.org/licenses/nonexclusive-distrib/1.0/ |
op_doi |
https://doi.org/10.48550/arxiv.2403.18038 |
_version_ |
1797569147928838144 |