A neural network and image processing technology are introduced for classifying woven fabric patterns. An autocorrelation function is used to determine one weave repeat of the fabric. The reflected fabric image is captured and digitized by the computer system. The learning vector quantization algorithm as a learning rule of the artificial neural network enables recognition of woven fabric types more effectively. The results demon strate that three fundamental weave types can be classified accurately, and structural parameters such as yarn spacing, its variance, and the ratio of warp spacing to weft spacing can also be obtained.
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