https://github.com/iago-suarez/fsg

:straight_ruler: :rocket: FSG: A statistical approach to line detection via fast segments grouping
https://github.com/iago-suarez/fsg

computer-vision image-processing line-detection line-segment-detector vanishing-points

Last synced: about 1 month ago
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:straight_ruler: :rocket: FSG: A statistical approach to line detection via fast segments grouping

• Host: GitHub
• URL: https://github.com/iago-suarez/fsg
• Owner: iago-suarez
• License: apache-2.0
• Created: 2021-09-10T11:21:05.000Z (over 3 years ago)
• Default Branch: main
• Last Pushed: 2021-12-01T20:02:51.000Z (about 3 years ago)
• Last Synced: 2024-04-16T07:13:58.226Z (8 months ago)
• Topics: computer-vision, image-processing, line-detection, line-segment-detector, vanishing-points
• Language: C++
• Homepage:
• Size: 3.71 MB
• Stars: 48
• Watchers: 6
• Forks: 9
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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# FSG: A statistical approach to line detection via fast segments grouping

This repository contains the source code of [FSG: A statistical approach to line detection via fast segments grouping](http://www.dia.fi.upm.es/~pcr/publications/iros2018.pdf). It allows merging segments extremely fast to fix broken detections and find large lines.

The method can be used with any line segment detector. We use LSD here, as it was done in the original paper.







### Compile and run

Instructions tested in Ubuntu 18.04:

```

sudo apt-get install build-essential libopencv-dev

mkdir build && cd build

cmake ..

make -j

./fsg_main

```

If everything goes well you should be able to see the following demo:

![Demo Result](images/demo-result.jpg)

### Cite

```bibtex

@inproceedings{suarez2018fsg,

  author={Su{\'a}rez, Iago and Mu{\~n}oz, Enrique and Buenaposada, Jos{\'e} M and Baumela, Luis},

  booktitle={2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, 

  title={FSG: A statistical approach to line detection via fast segments grouping}, 

  year={2018},

  pages={97-102},

  doi={10.1109/IROS.2018.8594434}

  }

```