The structure of nonwoven fabric has a great influence on the fabric properties, and the filtration performance of the fabric is determined by its pore structures and key parameters such as pore size, distribution and porosity, which should be described accurately and appropriately. However, at present problems exist in the methods of describing the three-dimensional structure of nonwovens, such as the high cost, slow speed and inaccurate model. This paper proposes a new method of reconstruction algorithm, inspired by the criss-cross internal structure of nonwovens. This nonwoven structure with a certain depth presents some implication of the processing information, which is similar to the formation of an anthill. The reconstructing processes are as follows. First, the multi-focused images of fibers are captured by the microscope and the images are then fused into a two-dimensional image. Second, the three-dimensional coordinate of the source point is calculated by the fiber segmentation and One-to-Many projection. Finally, the fiber axis is generated by connecting the source point according to the prescribed conditions, and then the closed three-dimensional surface is the three-dimensional path of a dynamic-radius sphere rolling along the fiber axis. The experiment results demonstrate that the proposed method can reconstruct the accurate structure of the nonwoven fabric and retain its vertical connection information, which is of great significance to the interception of harmful substances, the production and preparation of filter medium and the follow-up study of the filtration mechanism.

The filtration performance of nonwovens, such as virus protection and air purification, depends largely on their microstructure, that is, their internal structure. With the development of manufacturing techniques, nonwovens can be produced with complex microstructures to deliver low air resistance and high filtration efficiency. Therefore, it seems important to reconstruct an accurate three-dimensional (3D) model to describe the various microstructures for performance evaluation and product development. Multi-focus image fusion is one of the most effective ways used for the 3D nonwoven reconstruction. However, the overlapping and crossing of fibers in multi-focus images taken on an optional microscope make 3D fiber reconstruction incomplete and discontinuous. In this study, we developed a novel fiber segmentation and 3D nonwoven reconstruction algorithm to restore fiber continuity. The fiber web image was firstly thinned into the fiber mid-axis or skeleton, and fiber fragments were detected by searching the intersections. The features, such as the angle and depth, of each fiber fragment were obtained using Harris corner detection. A cluster technique was used to group the head-points of the fiber fragments that have similar features into one cluster. All fiber fragments in the same cluster are fitted with a polynomial curve to form a complete fiber in the 3D space. The experimental results show that this new method is suitable for the reconstruction of nonwovens with complex structures, such as fiber bonding or crossing, and can automatically detect and connect fiber fragments in 3D space. It provides an effective way for the subsequent simulation/evaluation of filtration characteristics.