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Automatic Tractor Guidance with Computer Vision
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English
Abstract
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.
Authors
Citation
Reid, J. and Searcy, S., "Automatic Tractor Guidance with Computer Vision," SAE Technical Paper 871639, 1987, https://doi.org/10.4271/871639.Also In
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