Segmentation of plants and weeds using infrared images
1996
Brivot, R. | Marchant, J.A.
The work presented here is part of a project whose goal is to guide automatically a vehicle long rows of crops in order to target herbicide or pesticide accurately on weeds or plants. This paper deals with the segmentation of near-infrared images for discriminating plants, weeds, and soil. The algorithm described has been developed with a real-time parallel implementation and a real agricultural environment in mind. This algorithm uses techniques based on hysteresis thresholding and region labelling methods, blob-filtering and mathematical morphology. It can provide information on the size and the position of plants and weed patches as well as information that could be used either for guiding the vehicle or tracking plants and weeds. Successful segmentation has been done on several image sequences in diffuse light conditions. We show that it is possible to discriminate plants, weeds, and soil for different fields of view.
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