Evaluating resin flow in natural fibre reinforced plastics using image analysis techniques

The precise characterization of resin flow in fiber reinforced plastic (FRP) systems is critical for optimizing permeability and ensuring uniform resin distribution, particularly in bio-based natural fiber composites. Insufficient resin infiltration can result in voids, fiber debonding, and compromised mechanical properties. Predicting and optimizing resin infiltration is essential to mitigating these defects and enhancing composite performance. This study presents an image analysis algorithm developed to quantify the resin impregnation behavior in natural fiber fabric under varying fiber orientations and controlled pressure conditions. By developing an image processing pipeline consisting of smoothing, thresholding, labeling, and refining techniques, the algorithm extracts key flow metrics, including flow front position and resin-saturated area after curing. The results provide insights into flow anisotropy, confirming that resin infiltration is significantly improved in fiber direction. To validate the algorithm, a hand-annotated dataset is created, serving as ground truth for comparison and evaluation. The findings highlight the correlation between visual observations and algorithm-based measurements, reinforcing the potential of automated image analysis in enhancing process control and permeability modeling for bio-based fiber reinforced plastics.