Plant leaf roughness analysis by texture classification with generalized fourier descriptors in a dimensionality reduction context

L. Journaux; M.F. Destain; F. Cointault; J. Miteran; A. Piron

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Plant leaf roughness analysis by texture classification with generalized fourier descriptors in a dimensionality reduction context

In: Precision agriculture '09

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L. Journaux

L. Journaux
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M.F. Destain

M.F. Destain
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F. Cointault

F. Cointault
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J. Miteran

J. Miteran
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A. Piron

A. Piron
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Type:: Chapter

Pages:: 213–220

DOI:: https://doi.org/10.1163/9789086866649_026

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Abstract

In the context of precision spraying research, this article explores the capacity and the performance of some combinations of pattern recognition and computer vision techniques applied to plant leaf roughness analysis. The techniques merge feature extraction, linear and nonlinear dimensionality reduction techniques and several kinds of classification methods. The performances are evaluated and compare in terms of the classification error. We concluded of the well performance of leaf roughness characterisation through the combination of Generalized Fourier Descriptors for feature extraction, SVM for classification method and Kernel-Discriminant for dimensionality reduction.

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Precision agriculture '09

E-Book ISBN:: 9789086866649

Publisher:: Wageningen Academic

Print Publication Date:: 01 Jan 2009

Subjects
- Life Sciences
  - General
  - Agriculture & Environment

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Plant leaf roughness analysis by texture classification with generalized fourier descriptors in a dimensionality reduction context

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Precision agriculture '09

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