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

Alexander Gillert, Bo Peters, Uwe Freiherr von Lukas, Jürgen Kreyling; Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops, 2021, pp. 1323-1331

Abstract


Semantic segmentation networks are prone to oversegmentation 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.

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[bibtex]
@InProceedings{Gillert_2021_ICCV, author = {Gillert, Alexander and Peters, Bo and von Lukas, Uwe Freiherr and Kreyling, J\"urgen}, title = {Identification and Measurement of Individual Roots in Minirhizotron Images of Dense Root Systems}, booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops}, month = {October}, year = {2021}, pages = {1323-1331} }