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Camera Calibration Algorithm for Tractor Vision Navigation

Published: 24 March 2021 Publication History

Abstract

The key to realize tractor visual navigation was obtained the actual three-dimensional coordinates of the corresponding points on the captured image. So the camera used to capture tractor tracks must be calibrated. In order to solve above problem, a camera calibration algorithm for tractor vision navigation was proposed. The algorithm which can meet the high real-time requirements of visual navigation was simple and accurate. The average error of camera calibration using this algorithm was 0.149157 pixels, the distortion coefficient was 0.184473, and the average calibration error was less than one thousandth.

References

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Reid J F, Zhang Q, Noguchi, al. 2000. Agriculture automatic guidance research in North America. Computers and Electronics in Agriculture, 25 (January, 2000), 155--167.
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Toru Torii. 2000. Research in autonomous agriculture vehicles in Japan. Computers and Electronics in Agriculture, 25 (January, 2005): 169--194.
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Bjorn Astrand, Albert-Jan Baerveldt. 2005. A vision based row-following system for agricultural field machinery. Mechatronics, 15 (Apirl, 2005): 251--269.
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Ehsami M R, Upadhyaya S K, Mattson M L. 2004. Seed location mapping using RTK GPS, Transactions of the CSAE. 47 (March, 2004), 909--914.

Cited By

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  • (2022)Computer Vision in Self-Steering TractorsMachines10.3390/machines1002012910:2(129)Online publication date: 11-Feb-2022

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  1. Camera Calibration Algorithm for Tractor Vision Navigation

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    EBIMCS '20: Proceedings of the 2020 3rd International Conference on E-Business, Information Management and Computer Science
    December 2020
    718 pages
    ISBN:9781450389099
    DOI:10.1145/3453187
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    In-Cooperation

    • Guilin: Guilin University of Technology, Guilin, China
    • International Engineering and Technology Institute, Hong Kong: International Engineering and Technology Institute, Hong Kong

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 24 March 2021

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    Author Tags

    1. Algorithm
    2. Camera calibration
    3. Visual navigation

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    • Research-article
    • Research
    • Refereed limited

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    EBIMCS 2020

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    EBIMCS '20 Paper Acceptance Rate 112 of 566 submissions, 20%;
    Overall Acceptance Rate 143 of 708 submissions, 20%

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    • (2022)Computer Vision in Self-Steering TractorsMachines10.3390/machines1002012910:2(129)Online publication date: 11-Feb-2022

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