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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1076387 | PMC |
| http://dx.doi.org/10.1073/pnas.20.4.232 | DOI Listing |
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The goal of achieving autonomous navigation for agricultural robots poses significant challenges, mostly arising from the substantial natural variations in crop row images as a result of weather conditions and the growth stages of crops. The processing of the detection algorithm also must be significantly low for real-time applications. In order to address the aforementioned requirements, we propose a crop row detection algorithm that has the following features: Firstly, a projective transformation is applied to transform the camera view and a color-based segmentation is employed to distinguish crop and weed from the background.
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