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

Abstract

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.