On the Improvement of Multiple Circles Detection from Images Using Hough Transform

Autores

  • Wesley Oliveira Barbosa UNIMONTES - Universidade Estadual de Montes Claros
  • Antonio Wilson Vieira UNIMONTES - Universidade Estadual de Montes Claros

DOI:

https://doi.org/10.5540/tema.2019.020.02.331

Palavras-chave:

Computer vision, Hough transform, Circle detection

Resumo

The automatic detection of lines and curves from color images is a very important task in many applications, such as object recognition and scene reconstruction. Although there are closed formulation for curve fitting to a set of points, if the point set describes more than one instance of the object, as two circles for example, there is no closed formulation for obtaining the individual set of parameters without a priori information of which points belong to each object. However, it is usual the presence of multiple instances of objects such as lines and circles on an image. The well known Hough Transform is an efficient tool for recovering multiple objects from images using a voting process where the usual presence of false positives is an issue. In our work, we present an improvement on the voting process to detect multiple circles using Hough Transform in order to avoid false positives. Our experiments show that our voting process leads to a more robust detection, reducing the number of false positive and providing a more accurate detection even with large number of circles.

Biografia do Autor

Antonio Wilson Vieira, UNIMONTES - Universidade Estadual de Montes Claros

CCET - Centro de Ciências e Tecnológicas

Referências

R. O. Duda and P. E. Hart, Use of the hough transformation to detect lines and curves in pictures, Communications ACM , vol. 15, no. 1, pp. 11-15, 1972.

P. Hough, Method and Means for Recognizing Complex Patterns. U.S. Patent 3.069.654, Dec. 1962.

E. R. Davies, Image space transforms for detecting straight edges in industrial images, Pattern Recognition Letters , vol. 4, no. 3, pp. 185-192, 1986.

F. Matsumoto and S. Tsuji, Detection of ellipses by a modifed hough trans

formation, IEEE Transactions on Computers , vol. 27, pp. 777-781, 08 1978.

C. Kimme, D. Ballard, and J. Sklansky, Finding circles by an array of accu

mulators, Commun. ACM , vol. 18, pp. 120-122, Feb. 1975.

L. Xu, E. Oja, and P. Kultanen, A new curve detection method: Randomized hough transform (rht)., Pattern Recognition Letters , vol. 11, no. 5, pp. 331-338, 1990

R. K. Yip, P. K. Tam, and D. N. Leung, Modification of hough transform for

circles and ellipses detection using a 2-dimensional array, Pattern Recognition , vol. 25, no. 9, pp. 1007-1022, 1992.

T.-C. Chen and K.-L. Chung, An efficient randomized algorithm for detecting circles, Computer Vision and Image Understanding , vol. 83, no. 2, pp. 172-191, 2001.

L. Pan, W. S. Chu, J. M. Saragih, F. D. la Torre, and M. Xie, Fast and ro

bust circular object detection with probabilistic pairwise voting, IEEE Signal

Processing Letters , vol. 18, pp. 639-642, Nov 2011.

A. O. Djekoune, K. Messaoudi, and M. Belhocine, A new modified hough

transform method for circle detection, in IJCCI 2013 - Proceedings of the

th International Joint Conference on Computational Intelligence, Vilamoura,

Algarve, Portugal, 20-22 September, 2013 , pp. 5-12, 2013.

E. V. C. Jiménez, D. Zaldivar, M. A. P. Cisneros, and M. A. Ramírez-Ortegón, Circle detection using discrete differential evolution optimization, Pattern Analysis and Applications , vol. 14, pp. 93-107, 2010.

J. Canny, A computational approach to edge detection, IEEE Trans. Pattern Anal. Mach. Intell. , vol. 8, pp. 679-698, June 1986

Downloads

Publicado

2019-07-29

Como Citar

Barbosa, W. O., & Vieira, A. W. (2019). On the Improvement of Multiple Circles Detection from Images Using Hough Transform. Trends in Computational and Applied Mathematics, 20(2), 331. https://doi.org/10.5540/tema.2019.020.02.331

Edição

Seção

Artigo Original