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Colour based detection of volunteer potatoes as weeds in sugar beet fields using machine vision
Authors:A. T. Nieuwenhuizen  L. Tang  J. W. Hofstee  J. Müller  E. J. van Henten
Affiliation:(1) Farm Technology Group, Wageningen University, P.O. Box 17, 6700 AA Wageningen, The Netherlands;(2) Department of Agricultural and Biosystems Engineering, Iowa State University, 203 Davidson Hall, Ames, IA, USA;(3) Institute of Agricultural Engineering, University of Hohenheim, Garbenstrasse 9, 70599 Stuttgart, Germany
Abstract:The possible spread of late blight from volunteer potato plants requires the removal of these plants from arable fields. Because of high labour, energy, and chemical demands, a method of automatic detection and removal is needed. The development and comparison of two colour-based machine vision algorithms for in-field volunteer potato plant detection in two sugar beet fields are discussed. Evaluation of the results showed that both methods gave closely matched results within fields, although large differences exist between the fields. At plant level, in one field up to 97% of the volunteer potato plants were correctly classified. In another field, only 49% of the volunteer plants were correctly identified. The differences between the fields were higher than the differences between the methods used for plant classification.
Keywords:Image analysis  Crop/weed classification  Plant-specific weed control
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