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Proceedings Paper

Analysis of straw row in the image to control the trajectory of the agricultural combine harvester (Erratum)
Author(s): Aleksandr Yurievich Shkanaev; Darya Alekseevna Krokhina; Dmitry Valerevich Polevoy; Aleksei Vladimirovich Panchenko; Dmitry Lvovitch Sholomov; Rinat Nailevish Sadekov
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Paper Abstract

Publisher’s Note: This paper, originally published on 13 April 2018, was replaced with a corrected/revised version on 14 September 2018. If you downloaded the original PDF but are unable to access the revision, please contact SPIE Digital Library Customer Service for assistance. The paper proposes a solution to the automatic operation of the combine harvester along the straw rows by means of the images from the camera, installed in the cab of the harvester. The U-Net is used to recognize straw rows in the image. The edges of the row are approximated in the segmented image by the curved lines and further converted into the harvester coordinate system for the automatic operating system. The “new” network architecture and approaches to the row approximation has improved the quality of the recognition task and the processing speed of the frames up to 96% and 7.5 fps, respectively. Keywords: Grain harvester,

Paper Details

Date Published: 13 April 2018
PDF: 10 pages
Proc. SPIE 10696, Tenth International Conference on Machine Vision (ICMV 2017), 1069602 (13 April 2018); doi: 10.1117/12.2310143
Show Author Affiliations
Aleksandr Yurievich Shkanaev, Cognitive Technologies Ltd. (Russian Federation)
JSC InterProgma (Russian Federation)
NUST MISIS (Russian Federation)
Darya Alekseevna Krokhina, Cognitive Technologies Ltd. (Russian Federation)
Dmitry Valerevich Polevoy, NUST MISIS (Russian Federation)
Aleksei Vladimirovich Panchenko, Cognitive Technologies Ltd. (Russian Federation)
Dmitry Lvovitch Sholomov, NUST MISIS (Russian Federation)
Institute for Information Transmission Problems (Russian Federation)
Rinat Nailevish Sadekov, MEI “Institute of Engineering Physics” (Russian Federation)

Published in SPIE Proceedings Vol. 10696:
Tenth International Conference on Machine Vision (ICMV 2017)
Antanas Verikas; Petia Radeva; Dmitry Nikolaev; Jianhong Zhou, Editor(s)

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