Virtual lines for offside situations analysis in football

  • Karim Ferreira Lima UNISINOS
  • Rodrigo Marques de Figueiredo UNISINOS
  • Eduardo Augusto Martins UNISINOS
  • Jean Schmith UNISINOS


Offside is one of the situations that is analyzed by the Video Assistant Referee (VAR). However, it has caused some controversy due to the delay in the analysis and definition of the irregularity. This work proposes a method that helps in the analysis of offside situations and also makes it available for nonprofessional matches. Here, image processing algorithms were used to determine offside situations in football matches from TV videos, of course, in accordance with the game regulation. The method includes the image vanishing point identification, camera calibration and the virtual offside line drawing. The method presented good results from 10 videos selected for analysis, with five from the right side of the field and five on from the left side. Among the videos, one was chosen as the basis for explaining the development of the method and demonstrate a situation with a virtual line drawn automatically, therefore determining an offside situation. As a result, the virtual line is identified by the color red when the manually selected player is in offside and green when he is not.
Palavras-chave: Football Offside, Virtual Offside Lines, VAR, Digital Image Processing


IFAB. The international football association board. laws of the game. football laws, rules and regulations. [Online]. Available:

S. Hashimoto and S. Ozawa, “A system for automatic judgment of offsides in soccer games,” in 2006 IEEE International Conference on Multimedia and Expo. IEEE, 2006, pp. 1889–1892.

T. D’Orazio, M. Leo, P. Spagnolo, P. L. Mazzeo, N. Mosca, M. Nitti, and A. Distante, “An investigation into the feasibility of real-time soccer offside detection from a multiple camera system,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 19, no. 12, pp. 1804– 1818, 2009.

G. Bradski, “The OpenCV Library,” Dr. Dobb’s Journal of Software Tools, 2000.

I. Sobel, “An isotropic 3 x 3 image gradient operator, machine vision for three-dimensional scenes, 376–379,” 1990.

J. Canny, “A computational approach to edge detection,” IEEE Transactions on pattern analysis and machine intelligence, no. 6, pp. 679–698, 1986.

M. Dubská, A. Herout, and J. Havel, “PClines — Line detection using parallel coordinates,” in CVPR 2011, 2011.

J. Havel, M. Dubská, A. Herout, and R. Josth, “Real-time detection of lines using parallel coordinates and CUDA,” Journal of real-time image processing, vol. 9, no. 1, pp. 205–216, 2014.

P. V. Hough, “Method and means for recognizing complex patterns,” Dec. 18 1962, uS Patent 3,069,654.

L. Alan, T. Vojír, L. C ehovin, J. Matas, and M. Kristan, “Discriminative correlation filter tracker with channel and spatial reliability,” International Journal of Computer Vision, vol. 126, no. 7, pp. 671–688, 2018.

F. Fédération Internationale de Football Association, Handbook of test methods for virtual offside line assessment, 2019.
LIMA, Karim Ferreira; FIGUEIREDO, Rodrigo Marques de; MARTINS, Eduardo Augusto; SCHMITH, Jean. Virtual lines for offside situations analysis in football. In: WORKSHOP DE TRABALHOS DA GRADUAÇÃO - CONFERENCE ON GRAPHICS, PATTERNS AND IMAGES (SIBGRAPI), 34. , 2021, Online. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2021 . p. 189-194. DOI: