Low-cost computer vision based automatic scoring of shooting targets

Authors:
Jacek Rudzinski;Marcin Luckner
Affiliations:
Faculty of Mathematics and Information Science, Warsaw University of Technology, Warsaw, Poland;Faculty of Mathematics and Information Science, Warsaw University of Technology, Warsaw, Poland
Venue:
KES'12 Proceedings of the 16th international conference on Knowledge Engineering, Machine Learning and Lattice Computing with Applications
Year:
2012

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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.