Python-Based Image Processing for Projected Void Quantification from SEM Fracture Surfaces

This dataset contains the Python image-processing code used for projected void quantification from SEM fracture-surface images. The workflow segments dark projected cavities, applies morphological filtering, separates clustered voids using distance-transform/watershed segmentation, and extracts quantitative descriptors including projected void area, equivalent diameter, aspect ratio, fill ratio, void count, void number density, and projected void area fraction. The routine also generates colored overlay images for visual validation and exports individual and summary void measurements as CSV files. The code was developed to support reproducible quantitative fractography of impact-fractured additively manufactured polymer-composite specimens.