Fiber Orientation Reconstruction from SEM Images of Fiber-Reinforced Composites

Abstract

The orientation of fibers in composites reinforced with short fibers can provide insight into the microstructure of the material and considerably affect its macroscopic characteristics. However, the present standard techniques for detecting fiber orientation and length based on microscopic image processing have faults in practical applications, including high effort, low efficiency, and unreliable measurement results. In this study, a method for measuring fiber orientation based on 3D reconstructions of scanning electron microscope (SEM) images is provided. The geodesic active contour (GAC) model is applied to segment the fibers in the SEM images. Matching the fiber contours with the scale-invariant feature transformation (SIFT) algorithm successfully extracts 3D orientation information from the fiber contours. The unit vector of the fiber axis is fitted from the extracted point cloud using the ordinary least squares (OLS) method. With a maximum deviation of 3.83° and an average deviation of 1.50°, the measurement findings of this method are substantially comparable to those of the image-measuring instrument. This paper offers a quantitative approach to studying the microstructure of short fiber-reinforced composites, thereby furnishing objective evidence to support the development and research of such materials.

Keywords

• fiber orientation
• SEM image 3D reconstruction
• image processing
• fiber-reinforced composite