A new system has been developed for Real-time image processing for crop/weed discrimination
in maize fields. The system consists of two independent subsystems, a fast image processing
delivering results in real-time (Fast Image Processing, FIP), and a slower and more accurate
processing (Robust Crop Row Detection, RCRD) thatis used to correct the first subsystem’s
mistakes. This combination produces a system that achieves very good results under a wide variety of conditions. Tested on several maize videos taken of different fields and during
different years, the system successfully detects an average of 95% of weeds and 80% of crops
under different illumination, soil humidity and weed/crop growth conditions. Moreover, the
system has been shown to produce acceptable results even under very difficult conditions, such
as in the presence of dramatic sowing errorsor abrupt camera movements. The computer
vision system has been developed for integration into a treatment system because the ideal
setup for any weed sprayer system would include a tool that could provide information on the
weeds and crops present at each point in real-time, while the tractor mounting the spraying bar
is moving (Burgos-Artizzu, et al., 2011).