Research on defect detection of complex textured fabric based on non-sampling discrete wavelet transform
In order to improve the defect recognition rate of complex textured fabric,a new algorithm was used to detect the defects of complex textured fabric.Firstly,the transform principle of unsampled discrete wavelet was analyzed,and two-dimensional unsampled wavelet was selected to detect fabric defects.Then,the selection basis of wavelet basis and decomposition scale was analyzed,and on this basis,the identification process of fabric defects was proposed.Finally,in order to verify the effectiveness of the non-sampling discrete wavelet transform algorithm,other mainstream algorithms were used for comparative analysis.Because the sampled discrete wavelet has translation invariant characteristics,the energy corresponding to the wavelet transform will increase in the defect region,while the energy will decrease in the non-defect region.Daubechies D2 wavelet was selected as the wavelet basis.The selection of wavelet decomposition scale should consider the texture characteristics of the fabric image,and the selected scale should be moderate.Three kinds of energy in horizontal,vertical and diagonal directions,were extracted from the fabric image region as characteristic values,and six types of fabric defects were selected respectively for comparative experiments.The experimental results show that the average accuracy and real-time detection speed of fabric defects detection using the non-sampling discrete wavelet transform algorithm are higher than other mainstream algorithms,and it can be better used for fabric defects detection with complex textures.
NETL
NSTL
万方数据
维普
