Fiber Recognition In Composite Materials
Xiang Li, Sara Shonkwiler, Sara McMains
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The accuracy of fiber recognition in cross-sectional scanned images is critical to material characterization for Fiber-Reinforced Polymer (FRP) composites. It is challenging to accurately detect and locate all fibers, especially broken fibers. We propose a two-step approach to automatically detect and categorize fibers. First we exploit distance-transform-based watershed segmentation to extract the boundaries of individual fiber cross-sections to handle cases where fibers contact each other, then use our proposed contour gradient charts to evaluate the breakage of each fiber cross-section and classify individual fiber boundaries as circles or ellipses. Our method accurately and robustly recognizes fibers in the cross-sectional images, whether they are aligned or misaligned, complete or broken.