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Proceedings Paper

Automated inspection of carpets
Author(s): Jian Wang; Rosemary A. Campbell; Ray J. Harwood
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Paper Abstract

A unified method for detecting all types of textural faults on a carpet using machine vision is presented. The Gaussian Markov Random Field (GMRF) model is used for the modelling of the textural surface of carpet. An experimental device using a line-scan camera and an IBM personal computer has been set up simulating on-line inspection of woven carpets to detect various types of fault arising in the production process. Measures for detecting faults are derived from the GMRF model based on sufficient statistics. This measure is very effective in detecting textural differences. Detection of unlevel, linear and other types of faults is discussed. In combination with our previous linear faults detection method, we have the confidence to be able to detect all types of textural faults on a plain carpet in an efficient way. With some additional techniques, this method can also be used for the detection of faults in colored pattern carpets.

Paper Details

Date Published: 6 January 1995
PDF: 12 pages
Proc. SPIE 2345, Optics in Agriculture, Forestry, and Biological Processing, (6 January 1995); doi: 10.1117/12.198873
Show Author Affiliations
Jian Wang, De Montfort Univ. (United Kingdom)
Rosemary A. Campbell, De Montfort Univ. (United Kingdom)
Ray J. Harwood, De Montfort Univ. (United Kingdom)

Published in SPIE Proceedings Vol. 2345:
Optics in Agriculture, Forestry, and Biological Processing
George E. Meyer; James A. DeShazer, Editor(s)

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