Sensing System Using Digital Photography Technique for Spot-Application of Herbicidein Pruned Wild Blueberry Fields

Abstract

<abstract><title><italic>Abstract. </italic></title> An automated sensing system consisting of hardware and software was developed for spot-application of herbicide in pruned wild blueberry fields. The hardware of the system consisted of a ruggedized PC, four digital cameras, a signal output unit, an 8-channel computerized variable rate controller (VRC), a flow controller, a pocket PC, solenoid valves, a servo valve, a flow meter, and nozzles mounted on an all-terrain vehicle. Custom software was developed in C++ and installed in the ruggedized PC to acquire images from the cameras and process in real-time to calculate the fraction of green pixels for weed detection in each image. Green contrast between weed and non-weed area in pruned wild blueberry fields was used to develop a robust and effective discriminating algorithm. Red-Green-Blue (RGB) images were converted to normalized green ratio binary images using the ratio of 255*G/(R+G+B) followed by segmentation for the discrimination. Custom software was capable of processing images to differentiate weed area from non-weed area in real-time and send the signal to the VRC to open the valve in the specific section of the boom where the weeds were detected. The normalized green ratio algorithm showed very reliable accuracy under different outdoor light conditions (>500 lux) and shade conditions. The sensing system performed well for accurate weed detection and for sending signals to the VRC for spraying the correct weed targets at up to 8 km h^-1 ground speed in the fields.