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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