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Rapid Detection of Multi-size Circular Shapes using Gradient Information and Signature Curve

by Mahdi Abbasi
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 182 - Number 44
Year of Publication: 2019
Authors: Mahdi Abbasi
10.5120/ijca2019918620

Mahdi Abbasi . Rapid Detection of Multi-size Circular Shapes using Gradient Information and Signature Curve. International Journal of Computer Applications. 182, 44 ( Mar 2019), 35-39. DOI=10.5120/ijca2019918620

@article{ 10.5120/ijca2019918620,
author = { Mahdi Abbasi },
title = { Rapid Detection of Multi-size Circular Shapes using Gradient Information and Signature Curve },
journal = { International Journal of Computer Applications },
issue_date = { Mar 2019 },
volume = { 182 },
number = { 44 },
month = { Mar },
year = { 2019 },
issn = { 0975-8887 },
pages = { 35-39 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume182/number44/30448-2019918620/ },
doi = { 10.5120/ijca2019918620 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:14:16.433143+05:30
%A Mahdi Abbasi
%T Rapid Detection of Multi-size Circular Shapes using Gradient Information and Signature Curve
%J International Journal of Computer Applications
%@ 0975-8887
%V 182
%N 44
%P 35-39
%D 2019
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The challenge of computational complexity reduction of Circular Hough Transforms (CHT) in detecting circular shapes in images is addressed. A new adaptive algorithm is introduced which minimizes the average accumulation space used in the voting process of CHT with the help of a variable size accumulation array. An improved method is presented which computes Signature Curve of gradient information of the image to find the radius and center of candidate circles, thus eliminating the influence of variable background intensity, especially in the noisy images. Experimental evaluations show that the proposed algorithm can significantly improve the quality of the results and considerably reduce the computational complexity and memory space.

References
  1. P. Mukhopadhyay and B. B. Chaudhuri, "A survey of Hough Transform," Pattern Recognition, vol. 48, pp. 993-1010, 2015/03/01/ 2015.
  2. J. Illingworth and J. Kittler, "A survey of the hough transform," Computer Vision, Graphics, and Image Processing, vol. 44, pp. 87-116, 1988/10/01/ 1988.
  3. T. D'Orazio, C. Guaragnella, M. Leo, and A. Distante, "A new algorithm for ball recognition using circle Hough transform and neural classifier," Pattern Recognition, vol. 37, pp. 393-408, 2004/03/01/ 2004.
  4. M. Y. Cao, C. H. Ye, O. Doessel, and C. Liu, "Spherical parameter detection based on hierarchical Hough transform," Pattern Recognition Letters, vol. 27, pp. 980-986, 2006/07/01/ 2006.
  5. R. Varun, Y. V. Kini, K. Manikantan, and S. Ramachandran, "Face Recognition Using Hough Transform Based Feature Extraction," Procedia Computer Science, vol. 46, pp. 1491-1500, 2015/01/01/ 2015.
  6. Y. Wang and G. Cheng, "Application of gradient-based Hough transform to the detection of corrosion pits in optical images," Applied Surface Science, vol. 366, pp. 9-18, 2016/03/15/ 2016.
  7. M. Sengupta and J. K. Mandal, "Authentication Through Hough Transformation Generated Signature on G-Let D3 Domain (AHSG)," Procedia Technology, vol. 10, pp. 121-130, 2013/01/01/ 2013.
  8. A. A. Kassim, Z. Mian, and M. A. Mannan, "Connectivity oriented fast Hough transform for tool wear monitoring," Pattern Recognition, vol. 37, pp. 1925-1933, 2004/09/01/ 2004.
  9. J. Cha, R. H. Cofer, and S. P. Kozaitis, "Extended Hough transform for linear feature detection," Pattern Recognition, vol. 39, pp. 1034-1043, 2006/06/01/ 2006.
  10. E. A. Murillo-Bracamontes, M. E. Martinez-Rosas, M. M. Miranda-Velasco, H. L. Martinez-Reyes, J. R. Martinez-Sandoval, and H. Cervantes-de-Avila, "Implementation of Hough transform for fruit image segmentation," Procedia Engineering, vol. 35, pp. 230-239, 2012/01/01/ 2012.
  11. M.-L. Torrente, S. Biasotti, and B. Falcidieno, "Recognition of feature curves on 3D shapes using an algebraic approach to Hough transforms," Pattern Recognition, vol. 73, pp. 111-130, 2018/01/01/ 2018.
  12. M. C. Beltrametti and L. Robbiano, "An algebraic approach to Hough transforms," Journal of Algebra, vol. 371, pp. 669-681, 2012/12/01/ 2012.
  13. M. Bernal-Marin and E. Bayro-Corrochano, "Integration of Hough Transform of lines and planes in the framework of conformal geometric algebra for 2D and 3D robot vision," Pattern Recognition Letters, vol. 32, pp. 2213-2223, 2011/12/01/ 2011.
  14. Tsuji and Matsumoto, "Detection of Ellipses by a Modified Hough Transformation," IEEE Transactions on Computers, vol. C-27, pp. 777-781, 1978.
  15. N. Kiryati, H. Kälviäinen, and S. Alaoutinen, "Randomized or probabilistic Hough transform: unified performance evaluation," Pattern Recognition Letters, vol. 21, pp. 1157-1164, 2000/12/01/ 2000.
  16. C. Galamhos, J. Matas, and J. Kittler, "Progressive probabilistic Hough transform for line detection," in Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149), 1999, pp. 554-560 Vol. 1.
  17. H. Kälviäinen, P. Hirvonen, L. Xu, and E. Oja, "Probabilistic and non-probabilistic Hough transforms: overview and comparisons," Image and Vision Computing, vol. 13, pp. 239-252, 1995/05/01/ 1995.
  18. A. Yla-Jaaski and N. Kiryati, "Adaptive termination of voting in the probabilistic circular Hough transform," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 16, pp. 911-915, 1994.
  19. N. Kiryati, Y. Eldar, and A. M. Bruckstein, "A probabilistic Hough transform," Pattern Recognition, vol. 24, pp. 303-316, 1991/01/01/ 1991.
  20. A. O. Djekoune, K. Messaoudi, and K. Amara, "Incremental circle hough transform: An improved method for circle detection," Optik, vol. 133, pp. 17-31, 2017/03/01/ 2017.
  21. Z. Yao and W. Yi, "Curvature aided Hough transform for circle detection," Expert Systems with Applications, vol. 51, pp. 26-33, 2016/06/01/ 2016.
  22. M. Ujaldón, A. Ruiz, and N. Guil, "On the computation of the Circle Hough Transform by a GPU rasterizer," Pattern Recognition Letters, vol. 29, pp. 309-318, 2008/02/01/ 2008.
  23. D. Ioannou, W. Huda, and A. F. Laine, "Circle recognition through a 2D Hough Transform and radius histogramming," Image and Vision Computing, vol. 17, pp. 15-26, 1999/01/01/ 1999.
  24. H. K. Yuen, J. Princen, J. Illingworth, and J. Kittler, "Comparative study of Hough Transform methods for circle finding," Image and Vision Computing, vol. 8, pp. 71-77, 1990/02/01/ 1990.
  25. H. Yang, J. Luo, Z. Shen, and W. Wu, "A local voting and refinement method for circle detection," Optik, vol. 125, pp. 1234-1239, 2014/02/01/ 2014.
  26. C. Kimme, D. Ballard, and J. Sklansky, "Finding circles by an array of accumulators," Commun. ACM, vol. 18, pp. 120-122, 1975.
Index Terms

Computer Science
Information Sciences

Keywords

Hough Transform Circle Detection Gradient Signature Curve

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