Comparison of Two Techniques of Pattern Recognition in the Image Analysis-Based Wheat Stalk Length Characterization

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Published: Jun 30, 2020
DOI: https://doi.org/10.1515/agriceng-2020-0011
Keywords:
wheat straw, ploughless tillage, stalk length determination, image analysis, flow lines-tracing

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Jan Thore Benthien
Thünen Institute of Wood Research, Leuschnerstraße 91, 21031, Hamburg, Germany
Sabrina Heldner
Thünen Institute of Wood Research, Leuschnerstraße 91, 21031, Hamburg, Germany
Benjamin Seppke
Cognitive Systems Laboratory, Department of Informatics, MIN Faculty, University of Hamburg, Vogt-Kölln-Straße 30, 22527, Hamburg, Germany
Jan Hörbelt
Faculty of Life Sciences, Rhine-Waal University of Applied Sciences, Marie-Curie-Straße 1, 47533, Kleve, Germany

Abstract

The chaff quality or, more specifically, the distribution of stalk length after straw shredding during wheat harvest with a combined harvester is of significant interest for ploughless tillage practices. The currently applied characterization methods (manual length measurement or the cascade sieve analysis) are time-consuming and labour-intensive. Image analysis-based size characterization has the potential to solve these problems. In this study, two techniques of digital image processing, the well-known method of image moments (rectangular model) and a sub-pixel skeletonization approach (flow lines-tracing), were applied comparatively for stalk length measurement. Upon applying the rectangular model, the analyzed stalks were found to be longer than when the flow lines-tracing algorithm was applied. This was attributed to the unbiased decision criteria of the measuring method. A greater length of the stalk is to be expected in the main stalk than when the length of a twisted or branched stalk is measured from the edge length of a rectangular box that encloses it.

Article Details

How to Cite
Benthien, J. T., Heldner, S., Seppke, B., & Hörbelt, J. (2020). Comparison of Two Techniques of Pattern Recognition in the Image Analysis-Based Wheat Stalk Length Characterization. Agricultural Engineering , 24(2), 1-8. https://doi.org/10.1515/agriceng-2020-0011
Issue
Vol. 24 No. 2 (2020)
Section
Articles

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