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European Journal of Wood and Wood Products

Erschienen in:

22.03.2017 | Original

Statistical feature extraction method for wood species recognition system

verfasst von: Imanurfatiehah Ibrahim, Anis Salwa Mohd Khairuddin, Hamzah Arof, Rubiyah Yusof, Effariza Hanafi

Erschienen in: European Journal of Wood and Wood Products | Ausgabe 1/2018

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Abstract

A cascaded wood species recognition system using simple statistical properties of the wood texture is presented where a total of 24 statistical features are extracted from each wood sample. They are mainly vessel features that allow a broad initial grouping of wood texture using fuzzy logic. Then, a neural network classifier is used to refine the broad grouping into the final wood species classification. The proposed system emulates the classification approach normally taken by human experts when analyzing wood species based on texture. A comprehensive set of experiments was performed on a database composed of 3000 macroscopic images of 30 different wood species to evaluate the effectiveness of the system. Finally, its performance is compared with previous works in terms of classification accuracy.

Vorheriger Artikel Reacted copper(II) concentrations in amine amended micronized copper treated red pine and lodgepole pine

Nächster Artikel Potential use of Libidibia ferrea and Poincianella pluviosa woods for bows of string instruments

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Titel: Statistical feature extraction method for wood species recognition system
verfasst von: Imanurfatiehah Ibrahim
Anis Salwa Mohd Khairuddin
Hamzah Arof
Rubiyah Yusof
Effariza Hanafi
Publikationsdatum: 22.03.2017
Verlag: Springer Berlin Heidelberg
Erschienen in: European Journal of Wood and Wood Products / Ausgabe 1/2018
Print ISSN: 0018-3768
Elektronische ISSN: 1436-736X
DOI: https://doi.org/10.1007/s00107-017-1163-1

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