%0 Journal Article %1 Hague2006 %A Hague, T. %A Tillett, N. %A Wheeler, H. %D 2006 %J Precision Agriculture %K machinevision %N 1 %P 21--32 %T Automated Crop and Weed Monitoring in Widely Spaced Cereals %U http://dx.doi.org/10.1007/s11119-005-6787-1 %V 7 %X Abstract  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 daylightillumination, was computed from the red, green and blue channels of a conventional CCD camera. The transformed image can besegmented into soil and vegetative components using a single fixed threshold. A previously reported algorithm was appliedto 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 assessmentof area density on the basis of high resolution plan view photographs of the same area; this was performed for views witha range of crop and weed levels. The correlation of the manual and automatic measures was examined, and used to obtain a calibrationfor the automatic approach. The results of mapping of a small field, at two times, are presented. The results of the automatedmapping appear to be consistent with manual assessment.

@article{Hague2006, abstract = {Abstract  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 daylightillumination, was computed from the red, green and blue channels of a conventional CCD camera. The transformed image can besegmented into soil and vegetative components using a single fixed threshold. A previously reported algorithm was appliedto 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 assessmentof area density on the basis of high resolution plan view photographs of the same area; this was performed for views witha range of crop and weed levels. The correlation of the manual and automatic measures was examined, and used to obtain a calibrationfor the automatic approach. The results of mapping of a small field, at two times, are presented. The results of the automatedmapping appear to be consistent with manual assessment.}, added-at = {2009-06-03T12:39:38.000+0200}, author = {Hague, T. and Tillett, N. and Wheeler, H.}, biburl = {https://www.bibsonomy.org/bibtex/2fd30a62a4584904dee11e28c54647b72/midtiby}, description = {SpringerLink - Journal Article}, interhash = {8d1c5e980f1ba8ac0ac0b43ba2449a57}, intrahash = {fd30a62a4584904dee11e28c54647b72}, journal = {Precision Agriculture}, keywords = {machinevision}, month = {#mar#}, number = 1, pages = {21--32}, timestamp = {2009-06-03T12:39:38.000+0200}, title = {Automated Crop and Weed Monitoring in Widely Spaced Cereals}, url = {http://dx.doi.org/10.1007/s11119-005-6787-1}, volume = 7, year = 2006 }