Crop Edge Detection Based on Stereo Vision

  • Johannes Kneip
  • Patrick FleischmannEmail author
  • Karsten Berns
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 867)


This paper proposes a robust detection method of uncut crop edges which is used for automated guidance of a combine harvester. The utilized stereo vision system allows for real-time depth perception of the environment. A three-dimensional elevation map of the terrain is constructed by the point cloud acquired in this way. The heights of crop and harvested areas are estimated using Expectation Maximization and segmented using of the clustering results. In a row-wise processing step, each scan line of heights is cross-correlated with a model function to compute possible candidate points located at the very crop edge. Using robust linear regression, a linear crop edge model is calculated, modeling the spatial distribution of the candidate points. An overall crop edge model is updated via exponentially weighted moving average.


Agricultural automation Computer vision for automation Visual-based navigation 


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Johannes Kneip
    • 1
  • Patrick Fleischmann
    • 1
    Email author
  • Karsten Berns
    • 1
  1. 1.Robotics Research Lab, Department of Computer ScienceTechnische Universität KaiserslauternKaiserslauternGermany

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