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Feature extraction for animal fiber identification

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conference contribution
posted on 2002-01-01, 00:00 authored by Lingxue KongLingxue Kong, Fenghua SheFenghua She, Saeid Nahavandi, Abbas KouzaniAbbas Kouzani
Fiber identification has been a very important task in many industries such as wool growing, textile processing, archaeology, histochernical engineering, and zoology. Over the years, animal fibers have been identified using physical and chemical approaches. Recently, objective identification of animal fibers has been developed based on the cuticular information of fibers. Effective and accurate extraction of representative features is essential to animal fiber identification and classification. In the current work, two different strategies are developed for this purpose. In the first method, explicit features are extracted using image processing. However, only implicit features are used in the second method with an unsupervised artificial neural network. It is found that the use of explicit features increases the accuracy of fiber identification but requires more effort on processing images and solid knowledge of what features are representative ones.

History

Event

International Conference on Image and Graphics (2nd : 2002 : Hefei, China)

Pagination

699 - 704

Publisher

SPIE, International Society for Optical Engineering

Location

Hefei, China

Place of publication

Bellingham, Wash.

Start date

2002-08-16

End date

2002-08-18

ISBN-10

0819446564

Language

eng

Publication classification

E1.1 Full written paper - refereed

Copyright notice

2002, SPIE, International Society for Optical Engineering

Editor/Contributor(s)

W Sui

Title of proceedings

SPIE 2002 : Proceedings of the 2nd International Conference on Image and Graphics