Structural characterization and measurement of nonwoven fabrics based on multi-focus image fusion

In the microscopic imaging process of multi-layered materials whose thickness is greater than the depth of the microscope, image blurring often occurs, so it is necessary to present some new methods to solve this problem. In this paper, a novel multi-focus image fusion algorithm and the related imaging system is proposed to improve the quality of fused image, which can be used to characterize the structure of the nonwoven fabrics. One set of single focus images captured with the same imaging geometry at different focus depth is merged into a well-focused image using the self-developed image fusion algorithm; it contributes to the subsequent investigation of structural characterization and measurement of nonwoven fabrics. The high and low frequency components of the image are filtered and combined using different fusion rules, the fusion image of the initial fabric is obtained after the fusion of multi-wavelets and the inverse transformation. Later, a set of image analysis algorithm is developed to measure the fiber diameter, orientation and porosity of nonwoven fabric. Our experimental results show that image-based measurements are effective compared to manual operation.