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.
%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
}