New Methods for Objective Evaluation of Fabric Pilling by Frequency Domain Image Processing

Abstract

Fabric pilling is a serious problem for the apparel industry. Resistance to pilling is normally tested by simulated accelerated wear and manual assessment of degree of pilling based on a visual comparison of the sample to a set of test images. A number of automated systems based on image analysis have been developed. The authors propose new methods of image analysis based on the two-dimensional wavelet transform to objectively measure the pilling intensity in sample images. Initial work employed the detail coefficients of the two-dimensional discrete wavelet transform (2DDWT) as a measure of the pilling intensity of woven/knitted fabrics.

This method is shown to be robust to image translation and brightness variation. Using the approximation coefficients of the 2DDWT, the method is extended to non-woven pilling image sets. Wavelet texture analysis (WTA) combined with principal components analysis are shown to produce a richer texture description of pilling for analysis and classification. Finally, employing the two-dimensional dual-tree complex wavelet transform as the basis for the WTA feature vector is shown to produce good automated classification on a range of standard pilling image sets.

Citation

Palmer, S., Zhang, J. and Wang, X. (2009), "New Methods for Objective Evaluation of Fabric Pilling by Frequency Domain Image Processing", Research Journal of Textile and Apparel, Vol. 13 No. 1, pp. 11-23. https://doi.org/10.1108/RJTA-13-01-2009-B002