Skip to content
A high-quality ellipse detector based on arc-support line segments which can both accurately and efficiently detect ellipses in images.
C++ MATLAB
Branch: master
Clone or download
Latest commit a1a314c Feb 24, 2020

Files

Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
pics Add files via upload Mar 2, 2019
LCS_ellipse.m renew Sep 30, 2018
README.md Update README.md Feb 24, 2020
drawEllipses.m renew Sep 30, 2018
ellipseDetectionByArcSupportLSs.m renew Sep 30, 2018
fitEllipse.m renew Sep 30, 2018
generateEllipseCandidates.cpp renew Oct 12, 2018

README.md

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. 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

  • The number of detected ellipses: 25; Running time: 0.460s; Resolution: 720 x 435

  • The number of detected ellipses: 3; Running time: 0.060s; Resolution: 512 x 456

  • The number of detected ellipses: 8; Running time: 0.110s; Resolution: 752 x 525

4.2 Detecting the ellipses with positive polarity

  • The number of detected ellipses: 4; Running time: 0.080s; Resolution: 752 x 525

4.3 Detecting the ellipses with negative polarity

  • The number of detected ellipses: 4; Running time: 0.086s; Resolution: 752 x 525

4.4 Detecting the ellipses sharing different polarity

  • The number of detected ellipses: 5; Running time: 0.226s; Resolution: 1000 x 680. ($T_{ac} = 165^{o}$, $T_r = 0.5$)

5. Successful Application Cases Up to Now

  • Car Wheel Hub Recognition
  • PCB Inspection
  • Object Fingerprinting
  • Robot Vision

6. 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={2019},
  publisher={IEEE}
}

7. Our Previous Work

We also proposed a circle detection method in our previous work which could detect circles from image efficiently, precisely and robustly.

You can’t perform that action at this time.