TY - GEN
T1 - Real-time ball detection and following based on a hybrid vision system with application to robot soccer field
AU - Shangari, Taher Abbas
AU - Shamshirdar, Faraz
AU - Azari, Bita
AU - Heydari, Mohammadhossein
AU - Sadeghnejad, Sourosh
AU - Baltes, Jacky
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2017.
PY - 2017
Y1 - 2017
N2 - Circle detection is one of the most important problems in image processing since circular objects, such as balls, are observed frequently in many natural and artificial environments and problems such as light variations, occlusions, shadows, circle-shaped objects, and real-time processing have to be managed. The previous methods are either edge-based which generally suffer from processing burden or color-based and cannot deal with color variations suitably. This paper presents a real-time ball detection framework that uses both color information and shape information together to detect and track a ball robustly. The results demonstrate superiority of the proposed method over the previous. After classifying the color space, image segmentation, building regions, and extracting objects, to reduce the computation, it is focused on finding the green horizon to eliminate a part of the image, which is beyond the field border. Afterward some filters based on circle-fitting methods, image moments are applied to detect and track the ball. The results show that these filters are real-time, robust against occlusion and are able to track the ball even for distances more than six meters.
AB - Circle detection is one of the most important problems in image processing since circular objects, such as balls, are observed frequently in many natural and artificial environments and problems such as light variations, occlusions, shadows, circle-shaped objects, and real-time processing have to be managed. The previous methods are either edge-based which generally suffer from processing burden or color-based and cannot deal with color variations suitably. This paper presents a real-time ball detection framework that uses both color information and shape information together to detect and track a ball robustly. The results demonstrate superiority of the proposed method over the previous. After classifying the color space, image segmentation, building regions, and extracting objects, to reduce the computation, it is focused on finding the green horizon to eliminate a part of the image, which is beyond the field border. Afterward some filters based on circle-fitting methods, image moments are applied to detect and track the ball. The results show that these filters are real-time, robust against occlusion and are able to track the ball even for distances more than six meters.
KW - Circle detection
KW - Circle-fitting method
KW - Color and shape information
KW - Real-time ball detection
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U2 - 10.1007/978-3-319-31293-4_42
DO - 10.1007/978-3-319-31293-4_42
M3 - Conference contribution
AN - SCOPUS:84978538772
SN - 9783319312910
T3 - Advances in Intelligent Systems and Computing
SP - 521
EP - 527
BT - Robot Intelligence Technology and Applications 4 - Results from the 4th International Conference on Robot Intelligence Technology and Applications
A2 - Karray, Fakhri
A2 - Kim, Jong-Hwan
A2 - Myung, Hyun
A2 - Jo, Jun
A2 - Sincak, Peter
PB - Springer Verlag
T2 - 4th International Conference on Robot Intelligence Technology and Applications, RiTA 2015
Y2 - 14 December 2015 through 16 December 2015
ER -