Research on the Fabric Defect Detection Method based on Improved PSO and NN Algorithm

This paper can reasonably identify the connection weight and threshold of NN and improve capability of true problem solution. This paper also applies PSO-BP NN model into classification of fabric flaws, decomposes the fabric image at single layer and extract the sub-image in horizontal and vertical direction to represent longitudinal and latitudinal texture by using orthogonal wavelet transform method and finally computes the feature values such as longitudinal and latitudinal energy, variance and entropy as the input of NN. By comparing the results of PSO-BP NN with the results of the BP NN, the results indicate that the PSO-BP NN can obtain a better effect.

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