Extraction of Yarn Positional Information from 3-D Voxel Data for Analysis of Textile Fabric Structure

In this paper, a novel method for analyzing a textile fabric structure is proposed to extract each yarn positional information of the textile fabric from 3-D voxel data made out of its X-ray computed tomography (CT) images. In order to extract the positional information, directions of filaments, of which yarn consists, are firstly estimated by correlating the voxel with a filament model. Each filament is secondly reconstructed by clustering the voxels of the filament using the estimated filament direction as a similarity. Then, each yarn is segmented by clustering the reconstructed filaments using a distance which is newly defined as a dissimilarity. The each yarn positional information is finally extracted by averaging all the filaments classified into the same yarn by the yarn segmentation. The effectiveness of the proposed method is confirmed by experimentally applying the method to voxel data of a sample plain woven fabric, which is made of a two-folded polyester yarn. The yarn positional information of each two-folded yarn is correctly extracted with the proposed method