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Path Recognition for Agricultural Robot Vision Navigation under Weed Environment

Abstract : In this paper, a path recognition method for agricultural robot vision navigation under weed environment is proposed. The vision navigation is based on color images sampled by a high speed camera. First, the crop and weed information is extracted using an appropriate color feature model to separate the green crop from background; then the image is thresholded, and the noise caused by weed is filtered by deleting small-area objects in the image; the navigation path is extracted through Hough transformation. Experiments are carried out in corn seedling field, and results show that the method can recognize navigation path correctly under weed environment.
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Peidong Wang, Zhijun Meng, Changhai Luo, Hebo Mei. Path Recognition for Agricultural Robot Vision Navigation under Weed Environment. 7th International Conference on Computer and Computing Technologies in Agriculture (CCTA), Sep 2013, Beijing, China. pp.242-248, ⟨10.1007/978-3-642-54344-9_30⟩. ⟨hal-01220921⟩



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