Identification and classification of animal fibres using artificial neural networks

She, F. H., Chow, S., Wang, B. and Kong, L. X. 2001, Identification and classification of animal fibres using artificial neural networks, Journal of textile engineering, vol. 47, no. 2, pp. 35-38.

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Title Identification and classification of animal fibres using artificial neural networks
Author(s) She, F. H.ORCID iD for She, F. H.
Chow, S.
Wang, B.
Kong, L. X.ORCID iD for Kong, L. X.
Journal name Journal of textile engineering
Volume number 47
Issue number 2
Start page 35
End page 38
Total pages 4 p.
Publisher Nihon Sen'i Kikai Gakkai
Place of publication Osaka-shi, Japan
Publication date 2001
ISSN 1346-8235
Summary It has been an important and challenging task to classify and evaluate the contents in wool blends. Quantitative characterisation of animal fibre scale patterns has attracted considerable attention, since it is the major evidence for identification and subsequent classification purpose. Although techniques such as imaging processing and linear demarcation functions have been used to identify unknown fibre type with some success, a more comprehensive approach is required to perform this task. In this paper, a new approach is presented, which employs non-linear demarcation functions by using an artificial neural network (ANN). Based on scale pattern features extracted by using image processing techniques the artificial neural network (ANN) model is to classify mohair and merino fibres. It is observed that the techniques developed in this work are very effective and have the potential to be applied to other animal fibres.
Language eng
Field of Research 091012 Textile Technology
Socio Economic Objective 860407 Wool Scouring and Top Making
HERDC Research category C1.1 Refereed article in a scholarly journal
Copyright notice ©2001, Nihon Sen'i Kikai Gakkai
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