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Sensors 2014, 14(2), 3001-3018; doi:10.3390/s140203001

Low-Cost 3D Systems: Suitable Tools for Plant Phenotyping

Institute of Geodesy and Geoinformation (IGG)—Geodesy, University of Bonn, Nussallee 17, Bonn 53115, Germany
Institute of Geodesy and Geoinformation (IGG)—Geoinformation, University of Bonn, Meckenheimer Allee 172, Bonn 53115, Germany
Institute for Crop Science and Resource Conservation (INRES)—Phytomedicine, University of Bonn, Nussallee 9, Bonn 53115, Germany
These authors contributed equally to this work.
Author to whom correspondence should be addressed.
Received: 12 December 2013 / Revised: 22 January 2014 / Accepted: 5 February 2014 / Published: 14 February 2014
(This article belongs to the Section Remote Sensors)
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Over the last few years, 3D imaging of plant geometry has become of significant importance for phenotyping and plant breeding. Several sensing techniques, like 3D reconstruction from multiple images and laser scanning, are the methods of choice in different research projects. The use of RGBcameras for 3D reconstruction requires a significant amount of post-processing, whereas in this context, laser scanning needs huge investment costs. The aim of the present study is a comparison between two current 3D imaging low-cost systems and a high precision close-up laser scanner as a reference method. As low-cost systems, the David laser scanning system and the Microsoft Kinect Device were used. The 3D measuring accuracy of both low-cost sensors was estimated based on the deviations of test specimens. Parameters extracted from the volumetric shape of sugar beet taproots, the leaves of sugar beets and the shape of wheat ears were evaluated. These parameters are compared regarding accuracy and correlation to reference measurements. The evaluation scenarios were chosen with respect to recorded plant parameters in current phenotyping projects. In the present study, low-cost 3D imaging devices have been shown to be highly reliable for the demands of plant phenotyping, with the potential to be implemented in automated application procedures, while saving acquisition costs. Our study confirms that a carefully selected low-cost sensor
Keywords: low-cost sensors; 3D imaging; David laser scanning system; Microsoft Kinect; parameterization; close-up scanning low-cost sensors; 3D imaging; David laser scanning system; Microsoft Kinect; parameterization; close-up scanning
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Paulus, S.; Behmann, J.; Mahlein, A.-K.; Plümer, L.; Kuhlmann, H. Low-Cost 3D Systems: Suitable Tools for Plant Phenotyping. Sensors 2014, 14, 3001-3018.

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