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:

    Sae Technical Papers


    Contributors:

    Conference:

    1987 SAE International Off-Highway and Powerplant Congress and Exposition ; 1987



    Publication date :

    1987-09-01




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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