Development of a machine vision system for a real-time precision sprayer

In the context of precision agriculture, we have developed a machine vision system for a real time precision sprayer. From a monochrome CCD camera located in front of the tractor, the discrimination between crop and weeds is obtained with an image processing based on spatial information using a Gabor filter. This method allows to detect the periodic signals from the non periodic one and it enables to enhance the crop rows whereas weeds have patchy distribution. Thus, weed patches were clearly identified by a blob-coloring method. Finally, we use a pinhole model to transform the weed patch coordinates image in world coordinates in order to activate the right electro-pneumatic valve of the sprayer at the right moment.

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