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Robot Intelligence Technology and Applications 4 pp 521–527Cite as

Real-Time Ball Detection and Following Based on a Hybrid Vision System with Application to Robot Soccer Field

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 447))

Abstract

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.

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Acknowledgment

The authors would like to thank the Humanoid and Medical Robotic Laboratory (HuMeR Lab) of Amirkabir Robotic Institute of Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran, and also Autonomous Agents Laboratory, University of Manitoba, Winnipeg, Canada. This research has been done in collaboration with both universities under the corporation protocol, started from 2014.

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Authors and Affiliations

  1. Bio-Inspired System Design Laboratory, Mechanical Engineering Department, Amirkabir University of Technology (Tehran Polytechnic), No. 424, Hafez Ave., P. O. Box 15875-4413, Tehran, 158754413, Iran

    Taher Abbas Shangari, Faraz Shamshirdar, Bita Azari, Mohammadhossein Heydari & Sourosh Sadeghnejad

  2. Autonomous Agents Laboratory, University of Manitoba, Winnipeg, R3T 2N2, Canada

    Jacky Baltes

Authors
  1. Taher Abbas Shangari
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  2. Faraz Shamshirdar
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  3. Bita Azari
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  4. Mohammadhossein Heydari
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  5. Sourosh Sadeghnejad
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  6. Jacky Baltes
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Corresponding author

Correspondence to Sourosh Sadeghnejad .

Editor information

Editors and Affiliations

  1. Electrical Engineering, Korea Advanced Institute of Science & Technology, Daejeon, Korea (Republic of)

    Jong-Hwan Kim

  2. Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, Ontario, Canada

    Fakhri Karray

  3. School of Information and Communication Technology, Griffith University, Gold Coast, Queensland, Australia

    Jun Jo

  4. Center for Intelligent Technologies, Technical University of Kosice, Kosice, Slovakia

    Peter Sincak

  5. Civil and Environmental Engineering, Korea Advanced Institute of Science & Technology, Daejeon, Korea (Republic of)

    Hyun Myung

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Shangari, T.A., Shamshirdar, F., Azari, B., Heydari, M., Sadeghnejad, S., Baltes, J. (2017). Real-Time Ball Detection and Following Based on a Hybrid Vision System with Application to Robot Soccer Field. In: Kim, JH., Karray, F., Jo, J., Sincak, P., Myung, H. (eds) Robot Intelligence Technology and Applications 4. Advances in Intelligent Systems and Computing, vol 447. Springer, Cham. https://doi.org/10.1007/978-3-319-31293-4_42

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  • DOI: https://doi.org/10.1007/978-3-319-31293-4_42

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-31291-0

  • Online ISBN: 978-3-319-31293-4

  • eBook Packages: EngineeringEngineering (R0)

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