Reference : Plant leaf roughness analysis by texture classification with generalized Fourier desc...
Scientific journals : Article
Engineering, computing & technology : Multidisciplinary, general & others
http://hdl.handle.net/2268/84744
Plant leaf roughness analysis by texture classification with generalized Fourier descriptors in a dimensionality reduction context
English
Journaux, L. mailto [ > > ]
Simon, J.-C. [ > > ]
Destain, Marie-France mailto [Université de Liège - ULg > Sciences et technologie de l'environnement > Mécanique et construction >]
Cointault, F. [ > > ]
Miteran, J. [ > > ]
Piron, Alexis mailto [Université de Liège - ULg > Gembloux Agro-Bio Tech > Gembloux Agro-Bio Tech >]
2011
Precision Agriculture
Springer
12
3
345-360
Yes (verified by ORBi)
International
1385-2256
1573-1618
Secaucus
NJ
[en] Texture classification ; Leaf roughness ; Precision spraying
[en] In the context of plant leaf roughness analysis for precision spraying, this study explores the capability and the performance of some combinations of pattern recognition and computer vision techniques to extract the roughness feature. The techniques merge feature extraction, linear and nonlinear dimensionality reduction techniques, and several kinds of methods of classification. The performance of the methods is evaluated and compared in terms of the error of classification. The results for the characterization of leaf roughness by generalized Fourier descriptors for feature extraction, kernel-based methods such as support vector machines for classification and kernel discriminant analysis for dimensionality reduction were encouraging. These results pave the way to a better understanding of the adhesion mechanisms of droplets on leaves that will help to reduce and improve the application of phytosanitary products and lead to possible modifications of sprayer configurations.
Researchers
http://hdl.handle.net/2268/84744
10.1007/s11119-010-9208-z

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