Novel measurement for multidirectional fabric wrinkling using wavelet analysis

• DOI: 10.1007/s12221-014-1337-y
• Publication Date: 2014-07-07T23:53:33Z
• Authors: Chengxia Liu; Yaqin Fu
• Keywords: Wrinkle; Woven fabric

Measuring and characterizing fabric wrinkling objectively and accurately is of vital importance because wrinkling behavior is one of the most important factors to determine visual aesthetic of fabrics and clothes. In this paper, a novel method for multidirectional fabric wrinkling measurement is presented. 12 fabrics with different fiber contents and weave structures are prepared and wrinkled by the new method. GLCM variables and standard deviation of wavelet decomposition coefficients are used to characterize fabric wrinkling. Results show that WRA (wrinkle recovery angle) does not have significant linear correlation with the GLCM variables (energy, entropy, contrast and correlation). The wavelet coefficient standard deviation at level 6 has the highest correlation with average WRA. The equations between average WRA and standard deviations can be used to predicate average WRA of a fabric conveniently, avoiding the time-consuming and tedious testing of WRA in each direction.