6 January 1995 Automated inspection of carpets
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Proceedings Volume 2345, Optics in Agriculture, Forestry, and Biological Processing; (1995); doi: 10.1117/12.198873
Event: Photonics for Industrial Applications, 1994, Boston, MA, United States
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.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jian Wang, Rosemary A. Campbell, Ray J. Harwood, "Automated inspection of carpets", Proc. SPIE 2345, Optics in Agriculture, Forestry, and Biological Processing, (6 January 1995); doi: 10.1117/12.198873; https://doi.org/10.1117/12.198873
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KEYWORDS
Inspection

Cameras

Digital signal processing

Algorithm development

Distance measurement

Image processing

Line scan image sensors

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