2013 |
Rudzinski, Jacek; Luckner, Marcin Low-cost computer vision based automatic scoring of shooting targets Inproceedings Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 185–195, 2013, ISSN: 03029743. Abstract | Links | BibTeX | Tagi: Computer vision, Hough transform, Pattern recognition, Score estimation @inproceedings{Rudzinski2013, title = {Low-cost computer vision based automatic scoring of shooting targets}, author = {Jacek Rudzinski and Marcin Luckner}, doi = {10.1007/978-3-642-37343-5_19}, issn = {03029743}, year = {2013}, date = {2013-01-01}, booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}, volume = {7828 LNAI}, pages = {185--195}, 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. ? 2013 Springer-Verlag.}, keywords = {Computer vision, Hough transform, Pattern recognition, Score estimation}, pubstate = {published}, tppubtype = {inproceedings} } 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. ? 2013 Springer-Verlag. |
Rudzinski, Jacek; Luckner, Marcin Low-cost computer vision based automatic scoring of shooting targets Inproceedings Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 185–195, 2013, ISSN: 03029743. Abstract | Links | BibTeX | Tagi: Computer vision, Hough transform, Pattern recognition, Score estimation @inproceedings{Rudzinski2013b, title = {Low-cost computer vision based automatic scoring of shooting targets}, author = {Jacek Rudzinski and Marcin Luckner}, doi = {10.1007/978-3-642-37343-5_19}, issn = {03029743}, year = {2013}, date = {2013-01-01}, booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}, volume = {7828 LNAI}, pages = {185--195}, 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. ? 2013 Springer-Verlag.}, keywords = {Computer vision, Hough transform, Pattern recognition, Score estimation}, pubstate = {published}, tppubtype = {inproceedings} } 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. ? 2013 Springer-Verlag. |
2012 |
Rudzinski, Jacek; Luckner, Marcin Automatic scoring of shooting targets with tournament precision Inproceedings Frontiers in Artificial Intelligence and Applications, pp. 324–334, 2012, ISSN: 09226389. Abstract | Links | BibTeX | Tagi: Computer vision, Hough transform, Pattern recognition, Score estimation @inproceedings{Rudzinski2012, title = {Automatic scoring of shooting targets with tournament precision}, author = {Jacek Rudzinski and Marcin Luckner}, doi = {10.3233/978-1-61499-105-2-324}, issn = {09226389}, year = {2012}, date = {2012-01-01}, booktitle = {Frontiers in Artificial Intelligence and Applications}, volume = {243}, pages = {324--334}, abstract = {This paper describes a computer vision based automatic scoring system of shooting targets. The system estimates scoring with a professional tournament precision, but is dedicated to amateur shooters and can work with photos taken by amateur cameras and mobile devices. The automatic scoring issue is divided into three problems: a target detection, a holes detection, and a hole analysis. The target is detected on the base of a bull-eye localization. The holes detection bases on the Hough transformation. The holes analysis localizes a position of hole's center. The position relative to detected scoring sections is a base for scoring. The proposed algorithm detects holes with 99 percent accuracy. An elimination of false positives results reduces the level of accepted holes to 92 percents. The average error for the automatic score estimation is 0.05 points. The estimation error for over 91 percent holes is lesser than a tournament-scoring threshold. textcopyright 2012 The authors and IOS Press. All rights reserved.}, keywords = {Computer vision, Hough transform, Pattern recognition, Score estimation}, pubstate = {published}, tppubtype = {inproceedings} } This paper describes a computer vision based automatic scoring system of shooting targets. The system estimates scoring with a professional tournament precision, but is dedicated to amateur shooters and can work with photos taken by amateur cameras and mobile devices. The automatic scoring issue is divided into three problems: a target detection, a holes detection, and a hole analysis. The target is detected on the base of a bull-eye localization. The holes detection bases on the Hough transformation. The holes analysis localizes a position of hole's center. The position relative to detected scoring sections is a base for scoring. The proposed algorithm detects holes with 99 percent accuracy. An elimination of false positives results reduces the level of accepted holes to 92 percents. The average error for the automatic score estimation is 0.05 points. The estimation error for over 91 percent holes is lesser than a tournament-scoring threshold. textcopyright 2012 The authors and IOS Press. All rights reserved. |
Rudzinski, Jacek; Luckner, Marcin Automatic scoring of shooting targets with tournament precision Inproceedings Frontiers in Artificial Intelligence and Applications, pp. 324–334, 2012, ISSN: 09226389. Abstract | Links | BibTeX | Tagi: Computer vision, Hough transform, Pattern recognition, Score estimation @inproceedings{Rudzinski2012b, title = {Automatic scoring of shooting targets with tournament precision}, author = {Jacek Rudzinski and Marcin Luckner}, doi = {10.3233/978-1-61499-105-2-324}, issn = {09226389}, year = {2012}, date = {2012-01-01}, booktitle = {Frontiers in Artificial Intelligence and Applications}, volume = {243}, pages = {324--334}, abstract = {This paper describes a computer vision based automatic scoring system of shooting targets. The system estimates scoring with a professional tournament precision, but is dedicated to amateur shooters and can work with photos taken by amateur cameras and mobile devices. The automatic scoring issue is divided into three problems: a target detection, a holes detection, and a hole analysis. The target is detected on the base of a bull-eye localization. The holes detection bases on the Hough transformation. The holes analysis localizes a position of hole's center. The position relative to detected scoring sections is a base for scoring. The proposed algorithm detects holes with 99 percent accuracy. An elimination of false positives results reduces the level of accepted holes to 92 percents. The average error for the automatic score estimation is 0.05 points. The estimation error for over 91 percent holes is lesser than a tournament-scoring threshold. textcopyright 2012 The authors and IOS Press. All rights reserved.}, keywords = {Computer vision, Hough transform, Pattern recognition, Score estimation}, pubstate = {published}, tppubtype = {inproceedings} } This paper describes a computer vision based automatic scoring system of shooting targets. The system estimates scoring with a professional tournament precision, but is dedicated to amateur shooters and can work with photos taken by amateur cameras and mobile devices. The automatic scoring issue is divided into three problems: a target detection, a holes detection, and a hole analysis. The target is detected on the base of a bull-eye localization. The holes detection bases on the Hough transformation. The holes analysis localizes a position of hole's center. The position relative to detected scoring sections is a base for scoring. The proposed algorithm detects holes with 99 percent accuracy. An elimination of false positives results reduces the level of accepted holes to 92 percents. The average error for the automatic score estimation is 0.05 points. The estimation error for over 91 percent holes is lesser than a tournament-scoring threshold. textcopyright 2012 The authors and IOS Press. All rights reserved. |
Publikacje
2013 |
Low-cost computer vision based automatic scoring of shooting targets Inproceedings Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 185–195, 2013, ISSN: 03029743. |
Low-cost computer vision based automatic scoring of shooting targets Inproceedings Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 185–195, 2013, ISSN: 03029743. |
2012 |
Automatic scoring of shooting targets with tournament precision Inproceedings Frontiers in Artificial Intelligence and Applications, pp. 324–334, 2012, ISSN: 09226389. |
Automatic scoring of shooting targets with tournament precision Inproceedings Frontiers in Artificial Intelligence and Applications, pp. 324–334, 2012, ISSN: 09226389. |