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Machine Vision and Applications
Erschienen in: Machine Vision and Applications 8/2013

01.11.2013 | Original Paper

Fuzzy logic-based pre-classifier for tropical wood species recognition system

verfasst von: Rubiyah Yusof, Marzuki Khalid, Anis Salwa Mohd Khairuddin

Erschienen in: Machine Vision and Applications | Ausgabe 8/2013

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Abstract

Classifying tropical wood species poses a considerable economic challenge and failure to classify the wood species accurately can have significant effects on timber industries. The problem of wood recognition is compounded with the nonlinearities of the features among the similar wood species. Besides that, large wood databases presented a problem of large processing time especially for online wood recognition system. In view of these problems, we propose the use of fuzzy logic-based pre-classifier as a means of treating uncertainty to improve the classification accuracy of tropical wood recognition system. The pre-classifier serve as a clustering mechanism for the large database simplifying the classification process making it more efficient. The use of the fuzzy logic-based pre-classifier has managed to increase the accuracy of the wood recognition system by 4 % and reduce the processing time for training and testing by more than 75 % and 26 % respectively.
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Metadaten
Titel
Fuzzy logic-based pre-classifier for tropical wood species recognition system
verfasst von
Rubiyah Yusof
Marzuki Khalid
Anis Salwa Mohd Khairuddin
Publikationsdatum
01.11.2013
Verlag
Springer Berlin Heidelberg
Erschienen in
Machine Vision and Applications / Ausgabe 8/2013
Print ISSN: 0932-8092
Elektronische ISSN: 1432-1769
DOI
https://doi.org/10.1007/s00138-013-0526-9

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