Automatic Inspection of Woven Fabric Density Based on Digital Image Analysis (Journal of Fiber Bioengineering and Informatics, 2015)
In order to inspect woven fabric density automatically, a method combining image processing and multiscale\rwavelet transform is proposed in this paper. Firstly, fabric images are pre-processed by Bimodal\rGaussian function histogram equalization to obtain more structure information. Secondly, fabric images\rare decomposed into horizontal and vertical sub-images by using wavelet filter. Thirdly, texture features\rare extracted from the sub-images through binarization and smooth processing. Finally, density of yarns\ris acquired accurately after analyzing features of warps and wefts of the fabric. The experiment results\rprove that the proposed algorithm is perfectly suitable for three principle weaves and the relative error\rof automatic inspection compared with manual inspection is less than 0.86%.
Keywords: Fabric Density; Woven Fabric; Wavelet Transform; Smooth Processing; Binarization