Fabric defect detection based on multi-scale wavelet transform and Gaussian mixture model method

This paper proposed an approach, which is based on multi-scale wavelet transform and Gaussian mixture model, to solve the problem about automated fabric defect detection and improve the quality of fabric in the production. Firstly, the sample image was tackled by the “Pyramid” wavelet decomposition algorithm, and the new images were obtained by reconstructing with the produced wavelet coefficients using wavelet thresholding denoising method. Secondly, the obtained new images were segmented by applying the Gaussian mixture model that was based on the Expectation–Maximization (EM) algorithm. Various fabric samples were used in the evaluation, and the experimental results showed that the designed algorithm could precisely locate the position of defect and segment the defect.

[1]  Du-Ming Tsai,et al.  Wavelet-based defect detection in solar wafer images with inhomogeneous texture , 2012, Pattern Recognit..

[2]  Michael K. Ng,et al.  Wavelet based methods on patterned fabric defect detection , 2005, Pattern Recognit..

[3]  P. Massart,et al.  From Model Selection to Adaptive Estimation , 1997 .

[4]  D. Rubin,et al.  Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .

[5]  S. Annadurai,et al.  Color Image Segmentation using Adaptive Spatial Gaussian Mixture Model , 2010 .

[6]  A. Ertuzun,et al.  Defect detection in textile fabric images using wavelet transforms and independent component analysis , 2006, Pattern Recognition and Image Analysis.

[7]  George Vachtsevanos,et al.  Fuzzy wavelets for feature extraction and failure classification , 1997 .

[8]  Kai-Ling Mak,et al.  Fabric defect detection using multi-level tuned-matched Gabor filters , 2012 .

[9]  K. L. Mak,et al.  An automated inspection system for textile fabrics based on Gabor filters , 2008 .

[10]  Stéphane Mallat,et al.  Multifrequency channel decompositions of images and wavelet models , 1989, IEEE Trans. Acoust. Speech Signal Process..

[11]  Wai Keung Wong,et al.  Stitching defect detection and classification using wavelet transform and BP neural network , 2009, Expert Syst. Appl..

[12]  Wing-Keung Wong,et al.  An intelligent model for detecting and classifying color-textured fabric defects using genetic algorithms and the Elman neural network , 2011 .