Objective Evaluation of Seam Pucker Using Complex Wavelet and Fractal Dimension of Textural Image
The 2-D dual-tree complex wavelet and fractal dimension of image texture is proposed to objective evaluation of seam pucker for the garment manufacturing. Because the complex 2-D dual-tree DWT also gives rise to wavelets in six distinct directions, extract feature of seam pucker is advantage over 2-D wavelet which only has four distinct directions. In terms of the theory of pattern recognition in an image process, Euclidean distance between seam pucker of sample clothes and standard template classified into five classes (AATCC method) on seam pucker is computed. Thus, automatic and objective class evaluation of seam pucker is realized, a practice example proves the method boosts the degree of accuracy of inspector than other methods.
W. Q. Song and J. Zhang, "Objective Evaluation of Seam Pucker Using Complex Wavelet and Fractal Dimension of Textural Image", Applied Mechanics and Materials, Vols. 44-47, pp. 3464-3468, 2011