Abstract
Circle detection is a critical issue in image analysis: it is undoubtedly a fundamental step in different application contexts, among them one of the most challenging is the detection of the ball in soccer game. Hough Transform based circle detector are largely used but there is a large open research area that attempt to provide more effective and less computationally expensive solutions based on randomized approaches, i.e. based on iterative sampling of the edge pixels. To this end, this work presents an ad-hoc randomized iterative work-flow, which exploits geometrical properties of isophotes, the curvature, to identify edge pixels belonging to the ball boundaries; this allow to consider a large amount of edge pixels, but limiting most of the time-consuming computation only on a restricted subset given by pixels with an high probability to lie on a circular structure. The method, coupled with a background suppression algorithm, has been applied to a set of real images acquired by fixed camera providing performances higher than a standard circular Hough transform solver, with a detection rate > 86 %.
Chapter PDF
Similar content being viewed by others
References
Davies, E.R.: Machine vision: theory, algorithms, practicalities. Morgan Kaufmann (2004)
D’Orazio, T., Leo, M.: A review of vision-based systems for soccer video analysis. Pattern Recognition 43(8), 2911–2926 (2010)
Mazzeo, P.L., Leo, M., Spagnolo, P., Nitti, M.: Soccer ball detection by comparing different feature extraction methodologies. Advances in Artificial Intelligence 6 (2012)
Chen, T.C., Chung, K.L.: An efficient randomized algorithm for detecting circles. Computer Vision and Image Understanding 83(2), 172–191 (2001)
Lichtenauer, J., Hendriks, E., Reinders, M.: Isophote properties as features for object detection. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR, vol. 2, pp. 649–654 (2005)
Canny, J.: A computational approach to edge detection. IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI 8(6), 679–698 (1986)
Spagnolo, P., D’Orazio, T., Leo, M., Distante, A.: Moving Object Segmentation by Background Subtraction and Temporal Analysis. Image and Vision Computing 24, 411–423 (2006)
Valenti, R., Gevers, T.: Accurate eye center location through invariant isocentric patterns. IEEE Transactions on Pattern Analysis and Machine Intelligence 34(9), 1785–1798 (2012)
Koenderink, J.J., van Doorn, A.J.: Surface shape and curvature scales. Image and Vision Computing 10(8), 557–564 (1992)
Chung, K.L., Huang, Y.H., Shen, S.M., Krylov, A.S., Yurin, D.V., Semeikina, E.V.: Efficient sampling strategy and refinement strategy for randomized circle detection. Pattern Recognition 45(1), 252–263 (2012)
Rousseeuw, P.J., Croux, C.: Alternatives to the median absolute deviation. Journal of the American Statistical Association 88(424), 1273–1283 (1993)
D’Orazio, T., Leo, M., Mosca, N., Spagnolo, P., Mazzeo, P.L.: A Semi-Automatic System for Ground Truth Generation of Soccer Video Sequences. In: 6th IEEE International Conference on Advanced Video and Signal Surveillance, Genoa, Italy (September 2009)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
De Marco, T., Leo, M., Distante, C. (2013). Soccer Ball Detection with Isophotes Curvature Analysis. In: Petrosino, A. (eds) Image Analysis and Processing – ICIAP 2013. ICIAP 2013. Lecture Notes in Computer Science, vol 8156. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41181-6_80
Download citation
DOI: https://doi.org/10.1007/978-3-642-41181-6_80
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-41180-9
Online ISBN: 978-3-642-41181-6
eBook Packages: Computer ScienceComputer Science (R0)