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  4. Identification and Measurement of Individual Roots in Minirhizotron Images of Dense Root Systems
 
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2021
  • Konferenzbeitrag

Titel

Identification and Measurement of Individual Roots in Minirhizotron Images of Dense Root Systems

Abstract
Semantic segmentation networks are prone to over segmentation in areas where objects are tightly clustered. In minirhizotron images with densely packed plant root systems this can lead to a failure to separate individual roots, thereby skewing the root length and width measurements. We propose to deal with this problem by adding additional output heads to the segmentation model, one of which is used with a ridge detection algorithm as an intermediate step and a second one that directly estimates root width. With this method we are able to improve detection and width measurements in densely packed roots systems without negative effects on sparse root systems.
Author(s)
Gillert, Alexander
Fraunhofer-Institut für Graphische Datenverarbeitung IGD
Peters, Bo
Greifswald Univ.
Lukas, Uwe von
Fraunhofer-Institut für Graphische Datenverarbeitung IGD
Kreyling, Jürgen
Greifswald Univ.
Hauptwerk
IEEE/CVF International Conference on Computer Vision Workshops, ICCVW 2021. Proceedings
Project(s)
DigIT!
Funder
Ministerium für Bildung, Wissenschaft und Kultur Mecklenburg-Vorpommern
Konferenz
International Conference on Computer Vision (ICCV) 2021
Workshop on Computer Vision in Plant Phenotyping and Agriculture (CVPPA) 2021
DOI
10.1109/ICCVW54120.2021.00153
File(s)
N-644060.pdf (3.9 MB)
Language
Englisch
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IGD
IGD-R
Tags
  • Lead Topic: Smart Cit...

  • Research Line: Comput...

  • computer vision

  • detection

  • segmentation

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