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Intelligent animal fiber classification with artificial neural networks

journal contribution
posted on 2002-01-01, 00:00 authored by Fenghua SheFenghua She, Lingxue KongLingxue Kong, Saeid Nahavandi, Abbas KouzaniAbbas Kouzani
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.


History

Journal

Textile research journal

Volume

72

Issue

7

Pagination

594 - 600

Publisher

Sage

Location

London, England

ISSN

0040-5175

eISSN

1746-7748

Language

eng

Publication classification

C1 Refereed article in a scholarly journal

Copyright notice

2002, SAGE Publications

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