Abstract
This paper introduces an automatic scoring algorithm on shooting target based on computer vision techniques. As opposed to professional solutions, proposed system requires no additional equipment and relies solely on existing straightforward image processing such as the Prewitt edge detection and the Hough transformation. Experimental results show that the method can obtain high quality scoring. The proposed algorithm detects holes with 99 percent, resulting in 92 percent after eliminating false positives. The average error on the automatic score estimation is 0.05 points. The estimation error for over 91 percent holes is lower than a tournament–scoring threshold. Therefore the system can be suitable for amateur shooters interested in professional (tournament-grade) accuracy.
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Rudzinski, J., Luckner, M. (2013). Low–Cost Computer Vision Based Automatic Scoring of Shooting Targets. In: Graña, M., Toro, C., Howlett, R.J., Jain, L.C. (eds) Knowledge Engineering, Machine Learning and Lattice Computing with Applications. KES 2012. Lecture Notes in Computer Science(), vol 7828. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37343-5_19
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DOI: https://doi.org/10.1007/978-3-642-37343-5_19
Publisher Name: Springer, Berlin, Heidelberg
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