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Intelligent animal fiber classification with artificial neural networks

She, F. H., Kong, L. X., Nahavandi, S. and Kouzani, A. Z. 2002, Intelligent animal fiber classification with artificial neural networks, Textile research journal, vol. 72, no. 7, pp. 594-600.

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Title Intelligent animal fiber classification with artificial neural networks
Author(s) She, F. H.
Kong, L. X.
Nahavandi, S.
Kouzani, A. Z.
Journal name Textile research journal
Volume number 72
Issue number 7
Start page 594
End page 600
Publisher Sage
Place of publication London, England
Publication date 2002
ISSN 0040-5175
Summary Artificial neural networks (ANN) are increasingly used to solve many problems related to pattern recognition and object classification. In this paper, we report on a study using artificial neural networks to classify two kinds of animal fibers: merino and mohair. We have developed two different models, one extracting nine scale parameters with image processing, and the other using an unsupervised artificial neural network to extract features automatically, which are determined in accordance with the complexity of the scale structure and the accuracy of the model. Although the first model can achieve higher accuracy, it requires more effort for image processing and more prior knowledge, since the accuracy of the ANN largely depends on the parameters selected. The second model is more robust than the first, since only raw images are used. Because only ordinary optical images taken with a microscope are employed, we can use the approach for many textile applications without expensive equipment such as scanning electron microscopy.


Language eng
Field of Research 080108 Neural, Evolutionary and Fuzzy Computation
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2002 by SAGE Publications
Persistent URL http://hdl.handle.net/10536/DRO/DU:30001773

Document type: Journal Article
Collection: School of Engineering and Technology
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