Neural networks for the optical recognition of defects in cloth

Anno: 1996

Autori: Hoffer L. M., Francini F., Tiribilli B., Longobardi G.

Affiliazione autori: Istituto Nazionale di Ottica, Largo E. Fermi 6, 50125 Firenze, Italy

Abstract: A fast system to reveal the presence and type of fabric defects during the weaving process is developed. Since the fabric is similar to a 2-D grid, its defects are clearly observed in the changes in its optical Fourier transform (OFT), which appears stationary while the fabric is moving across the loom. Previous work, based on the statistical parameters of the OFT, showed that the presence of faults can be detected when only global changes in the images are considered. We show that by selecting a small subset of pixels from the image as input to a neural network, fabric defects can not only be detected but also successfully identified. A knowledge-based system could conceivably be constructed to use this information to resolve problems with the loom in real time, without the need for operator intervention. (C) 1996 Society of Photo-Optical Instrumentation Engineers.

Giornale/Rivista: OPTICAL ENGINEERING

Volume: 35 (11)      Da Pagina: 3183  A: 3190

Parole chiavi: neural networks; optical Fourier transform; textile; pattern recognition;
DOI: 10.1117/1.601057

Citazioni: 29
dati da “WEB OF SCIENCE” (of Thomson Reuters) aggiornati al: 2024-02-25
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