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Plant Phenotyping Using DLT Method: Towards Retrieving the Delicate Features in a Dynamic Environment

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Towards Autonomous Robotic Systems (TAROS 2023)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14136))

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Abstract

Passive phenotyping methodologies use various techniques for calibration, which include a variety of sensory information like vision. Contrary to the state-of-the-art, this paper presents the use of a Direct Linear Transformation (DLT) algorithm to find the shape and position of fine and delicate features in plants. The proposed method not only finds a solution to the motion problem but also provides additional information related to the displacement of the traits of the subject plant. This study uses DLTdv digitalisation toolbox to implement the DLT modelling tool which reduces the complications in data processing. The calibration feature of the toolbox also enables the prior assumption of calibrated space in using DLT.

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Acknowledgements

The authors would like to people the strawberry growing facility at the University of Lincoln for providing help towards collecting the data. This research is fully funded by the Lincoln Agri-Robotics (LAR), University of Lincoln as part of the PhD process of Srikishan Vayakkattil. The research had added support from Research England.

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Authors and Affiliations

  1. Lincoln Institute for Agri-Food Technology, College of Science, University of Lincoln, Lincoln, LN2 2LG, UK

    Srikishan Vayakkattil, Grzegorz Cielniak & Marcello Calisti

Authors
  1. Srikishan Vayakkattil
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  2. Grzegorz Cielniak
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  3. Marcello Calisti
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Corresponding author

Correspondence to Srikishan Vayakkattil .

Editor information

Editors and Affiliations

  1. University of Cambridge, Cambridge, UK

    Fumiya Iida

  2. University of Oxford, Oxford, UK

    Perla Maiolino

  3. University of Cambridge, Cambridge, UK

    Arsen Abdulali

  4. Brunel University London, Uxbridge, UK

    Mingfeng Wang

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Vayakkattil, S., Cielniak, G., Calisti, M. (2023). Plant Phenotyping Using DLT Method: Towards Retrieving the Delicate Features in a Dynamic Environment. In: Iida, F., Maiolino, P., Abdulali, A., Wang, M. (eds) Towards Autonomous Robotic Systems. TAROS 2023. Lecture Notes in Computer Science(), vol 14136. Springer, Cham. https://doi.org/10.1007/978-3-031-43360-3_1

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  • DOI: https://doi.org/10.1007/978-3-031-43360-3_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-43359-7

  • Online ISBN: 978-3-031-43360-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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