Automated classification of wood transverse cross-section micro-imagery from 77 commercial Central-African timber species

• Key message Pattern recognition has become an important tool to aid in the identification and classification of timber species. In this context, the focus of this work is the classification of wood species using texture characteristics of transverse cross-section images obtained by microscopy. The...

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Veröffentlicht in:	Annals of forest science. 2017-06, Vol.74 (2), p.1-14, Article 30
Hauptverfasser:	Rosa da Silva, Núbia, De Ridder, Maaike, Baetens, Jan M., Van den Bulcke, Jan, Rousseau, Mélissa, Martinez Bruno, Odemir, Beeckman, Hans, Van Acker, Joris, De Baets, Bernard
Format:	Artikel
Sprache:	eng
Schlagworte:	Biomedical and Life Sciences Classification Commercial species Cross-sections Diagnostic systems Discriminant analysis Environment Feature extraction Forestry Forestry Management Image classification Image quality Life Sciences Machine vision Measurement Microscopy Original Paper Pattern recognition Species classification Species richness Texture Tree Biology Trees Vegetation patterns Wood Science & Technology
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