Conics Detection Method based on Pascal’s Theorem

Musfequs Salehin, Lihong Zheng, Junbin Gao

Abstract

This paper presents a novel conics detection method that can be applied for real images. The existing methods usually detect either circular or elliptical, or parabolic shape at one operation. Most of them need the information about center, radius, major axis, minor axis, vertex, and more. In our proposed method, the tangents on curve segments, conic parts, and conics are constructed using Pascal’s theorem. The conic parts can be used to detect different types of conic sections from an image. The performance of the proposed method has been tested on the sample images selected from Caltech-256 database and various types of conic sections can be identified from the real images compared to other method.

References

  1. Akinlar, C. & Topal, C., 2013. EDCircles: A real-time circle detector with a false detection control. Pattern Recognition, 46(3), pp.725-740.
  2. Alajlan, N. et al., 2007. Shape retrieval using triangle-area representation and dynamic space warping. Pattern Recognition, 40(7), pp.1911-1920.
  3. Chia, A. & Rahardja, S., 2011. A split and merge based ellipse detector with self-correcting capability. Image Processing, IEEE Transaction on, 20(7), pp.1991- 2006.
  4. Coxeter, H. & Greitzer, S., 1967. Geometry revisited, Mathematical Association of America Washington, DC.
  5. Griffin, G., Holub, A. & Perona, P., 2007. Caltech-256 object category dataset.
  6. Kovesi, P.D., 2000. MATLAB and Octave functions for computer vision and image processing. Online: http://www. csse. uwa. edu. au/ pk/Research/MatlabFns/# match.
  7. McLaughlin, R.A., 2000. Intelligent algorithms for finding curves and surfaces in real world data, PhD Thesis, Department of Electrical and Electronic Engineering, University of Western Australia, 2000.
  8. Prasad, D.K., Leung, M.K.H. & Cho, S.-Y., 2012. Edge curvature and convexity based ellipse detection method. Pattern Recognition, 45(9), pp.3204-3221.
  9. Qiao, Y. & Ong, S.H., 2007. Arc-based evaluation and detection of ellipses. Pattern recognition, 40(7), pp.1990-2003.
  10. Wong, C. & Lin, S., 2012. A survey on ellipse detection methods. Industrial Electronics (ISIE), 2012 IEEE International Symposium on, pp.1105-1110.
  11. Xu, L., Oja, E. & Kultanen, P., 1990. A new curve detection method: randomized Hough transform (RHT). Pattern recognition letters, 11(5), pp.331-338.
Download


Paper Citation


in Harvard Style

Salehin M., Zheng L. and Gao J. (2015). Conics Detection Method based on Pascal’s Theorem . In Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2015) ISBN 978-989-758-089-5, pages 491-497. DOI: 10.5220/0005299804910497


in Bibtex Style

@conference{visapp15,
author={Musfequs Salehin and Lihong Zheng and Junbin Gao},
title={Conics Detection Method based on Pascal’s Theorem},
booktitle={Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2015)},
year={2015},
pages={491-497},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005299804910497},
isbn={978-989-758-089-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2015)
TI - Conics Detection Method based on Pascal’s Theorem
SN - 978-989-758-089-5
AU - Salehin M.
AU - Zheng L.
AU - Gao J.
PY - 2015
SP - 491
EP - 497
DO - 10.5220/0005299804910497