Image processing techniques were investigated for developing a guidance signal for a tractor operating on agricultural row crops. The guidance signal was computed from thresholded images segmented by a Bayes classifier. The distribution of crop canopy and soil background pixels in an image was approximated with a bimodal Gaussian distribution function. The parameters of the distribution were estimated by regression to systematically subsampled images. Run-length encoding was used to locate center points of row crop canopy blobs in the thresholded images. A heuristic line detection algorithm was used to determine the parameters defining crop row location on the image plane. Row parameters were used to compute a tractor guidance signal. Results are presented on the performance of the individual components of the algorithm.


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    Title :

    Automatic tractor guidance with computer vision


    Additional title:

    Automatische Radschlepperfuehrung mit Computer-Bildverarbeitung


    Contributors:
    Reid, J.F. (author) / Searcy, S.W. (author)

    Published in:

    SAE-Papers ; Sep ; 1-21


    Publication date :

    1987


    Size :

    21 Seiten, 13 Bilder, 9 Tabellen, 30 Quellen


    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




    Automatic Tractor Guidance with Computer Vision

    Reid, John F. / Searcy, Stephen W. | SAE Technical Papers | 1987


    Automatic tractor guidance with computer vision

    Reid,J.F. / Saercy,S.W. / Univ.of Illinois,Agricultural Engineering Dep.,US et al. | Automotive engineering | 1987


    Vision assisted tractor guidance for agricultural vehicles

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    Vision assisted tractor guidance for agricultural vehicles

    Brandon, J.R. / Searcy, S.W. | Tema Archive | 1992


    Vision Assisted Tractor Guidance for Agricultural Vehicles

    Brandon, J. Robert / Searcy, Stephen W. | SAE Technical Papers | 1992