High-quality-ellipse-detection

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High-quality-ellipse-detection

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A high-quality ellipse detector based on arc-support line segments which can both accurately and efficiently detect ellipses in images.

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최종 버전 다운로드 (.zip)

- 13.jpg
- 23.bmp
- 23_result.jpg
- 27.jpg
- 27_result.jpg
- 35.jpg
- 43.jpg
- 43_result.jpg
- 666.jpg
- 666_negative.jpg
- 666_positive.jpg
- 666_result.jpg
- different-polarity-detection_all.jpg
- im9933.jpg
CC-BY-SA-NC-license.txt
drawEllipses.m
ellipseDetectionByArcSupportLSs.m
fitEllipse.m
generateEllipseCandidates.cpp
LCS_ellipse.m
README.md

// repository documentation

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# High-quality Ellipse Detection
## 1. Illustration
- This is the source code for the paper [Arc-support Line Segments Revisited: An Efficient and High-quality Ellipse Detection](https://arxiv.org/abs/1810.03243). ***Important: Please use the citation of our IEEE TIP version instead of arXiv version***.
- The main contribution of the proposed ellipse detector is to both accurately and efficiently detect ellipses in images, which is universally considered as a tough and long-standing problem in ellipse detection field. The proposed ellipse detector owns the features of *high localization accuracy, efficiency, robustness*, and *stability*, which comprehensively yields high-quality ellipse detection performance in front of real-world images. 
- There are only *two* extrinsic parameters, namely the elliptic angular coverage $T_{ac}$ and the ratio of support inliers $T_{r}$, which enables the proposed ellipse detector to be conveniently used and applied in real applications. In addition, the *specified_polarity* option can help users find the polarity-specific ellipses in the image. The default parameters $T_{ac} = 165^o$ and $T_{r} = 0.6$ are used for comparison experiments in our paper.  
- The source code is free for academic use. Please cite our paper if you use the source code, thanks.

## 2. Requirements
- MATLAB
- OpenCV (Version 2.4.9)
- 64-bit Windows Operating System

## 3. How to use
- Firstly, compile the file "generateEllipseCandidates.cpp" in MATLAB on your computer to generate the mex file "generateEllipseCandidates.mexw64" with the following command:  
  
  ---
  mex generateEllipseCandidates.cpp -IF:\OpenCV\opencv2.4.9\build\include -IF:\OpenCV\opencv2.4.9\build\include\opencv -IF:\OpenCV\opencv2.4.9\build\include\opencv2 -LF:\OpenCV\opencv2.4.9\build\x64\vc11\lib -IF:\Matlab\settlein\extern\include -LF:\Matlab\settlein\extern\lib\win64\microsoft -lopencv_core249 -lopencv_highgui249 -lopencv_imgproc249 -llibmwlapack.lib  
  
  ---
  Notably, the corresponding software paths of OpenCV and MATLAB, namely the "F:\OpenCV\opencv2.4.9\" and "F:\Matlab\settlein\", should be replaced to your own.  
- Secondly, run the demo file "LCS_ellipse.m".

## 4. Examples
*Some high-quality ellipse detection examples run with default parameters and on the same computer with Intel Core i7-7500U 2.7GHz CPU and 8 GB memory*

### 4.1 Detecting all ellipses in the image

---
- The number of detected ellipses: 4; Running time: 0.090s; Resolution: 651 x 436
  <img src="./pics/43_result.jpg" width="73%" height="73%">  
  
---
- The number of detected ellipses: 25; Running time: 0.460s; Resolution: 720 x 435
  <img src="./pics/27_result.jpg" width="73%" height="73%">

---
- The number of detected ellipses: 3; Running time: 0.060s; Resolution: 512 x 456
  <img src="./pics/23_result.jpg" width="73%" height="73%">

---
- The number of detected ellipses: 8; Running time: 0.110s; Resolution: 752 x 525
  <img src="./pics/666_result.jpg" width="73%" height="73%">

### 4.2 Detecting the ellipses with positive polarity  
- The number of detected ellipses: 4; Running time: 0.080s; Resolution: 752 x 525
  <img src="./pics/666_positive.jpg" width="73%" height="73%">

### 4.3 Detecting the ellipses with negative polarity
- The number of detected ellipses: 4; Running time: 0.086s; Resolution: 752 x 525
  <img src="./pics/666_negative.jpg" width="73%" height="73%">

### 4.4 Detecting the ellipses sharing different polarity  
- The number of detected ellipses: 5; Running time: 0.226s; Resolution: 1000 x 680. ($T_{ac} = 165^{o}$, $T_r = 0.5$)  
  <img src="./pics/different-polarity-detection_all.jpg" width="73%" height="73%">

## 5. Successful Application Cases Up to Now
- Car Wheel Hub Recognition
- PCB Inspection
- Object Fingerprinting
- Robot Vision

## 6. Some Excellent Re-implementations
- [C++ implementation](https://github.com/memory-overflow/standard-ellipse-detection) @ GitHub user `memory-overflow`

## 7. Citation
```
@article{lu2019arc,
  title={Arc-Support Line Segments Revisited: An Efficient High-Quality Ellipse Detection},
  author={Lu, Changsheng and Xia, Siyu and Shao, Ming and Fu, Yun},
  journal={IEEE Transactions on Image Processing},
  volume={29},
  pages={768--781},
  year={2020},
  publisher={IEEE}
}
```

## 8. Our Previous Work  
We also proposed a [circle detection method](https://github.com/AlanLuSun/Circle-detection) in our previous work which could detect circles from image efficiently, precisely and robustly.

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