Automated crop and weed monitoring in widely spaced cereals

An approach is described for automatic assessment of crop and weed area in images of widely spaced (0.25 m) cereal crops, captured from a tractor mounted camera. A form of vegetative index, which is invariant over the range of natural daylight illumination, was computed from the red, green and blue channels of a conventional CCD camera. The transformed image can be segmented into soil and vegetative components using a single fixed threshold. A previously reported algorithm was applied to robustly locate the crop rows. Assessment zones were automatically positioned; for crop growth directly over the crop rows, and for weed growth between the rows. The proportion of crop and weed pixels counted was compared with a manual assessment of area density on the basis of high resolution plan view photographs of the same area; this was performed for views with a range of crop and weed levels. The correlation of the manual and automatic measures was examined, and used to obtain a calibration for the automatic approach. The results of mapping of a small field, at two times, are presented. The results of the automated mapping appear to be consistent with manual assessment.