This paper presents a novel cross-sectional methodology for characterizing the tensile properties of bast fibers, demonstrated on two types of hemp fibers with differing levels of separation. A Hessian-based ridge detection algorithm and a 3D microscope based method were employed to accurately identify fiber edges from microscopic images, enabling precise diameter and cross-sectional measurements. A comparative analysis with a gravimetric reference method demonstrated that the cross-sectional approach exhibited reduced variability, suggesting improved precision and reproducibility. Additionally, these methodologies offer greater cost efficiency compared to high-cost imaging techniques such as computed tomography. These findings underscore the potential of cross-sectional imaging techniques, combined with robust edge-detection algorithms, to provide cost-effective, reproducible, and precise fiber characterization for industrial applications in textiles and fiber-reinforced composites.