Abstract:

In order to reduce the amount of computation, fabric features were extracted after the gray value of fabric texture image was projected on one-dimensional time series along vertical and lateral direction. Fisher’s criterion was used to evaluate the discrimination between the defect samples and the normal samples. Two features of certain complementarity and great discrimination were chosen to detect defects on seven fabrics of different texture background. The experimental result showed that the false alarm rate and missing rate could be controlled below10% within a certain range of threshold values，which indicated the proposed method was efficient in reducing the amount of fractal dimension computation greatly as well as differentiating normal and defect texture.