Benchmarking image processing techniques for porosity measurement in polymer additive manufacturing: Review and experimental analysis

Chawla, Komal; Talabi, Segun Isaac; Rodriguez, Brittany; Kumar, Vipin; Kim, Seokpum; Kunc, Vlastimil; Hassen, Ahmed Arabi

doi:10.1016/j.compositesb.2025.112857

Benchmarking image processing techniques for porosity measurement in polymer additive manufacturing: Review and experimental analysis

Journal Article · Tue Jul 29 00:00:00 EDT 2025 · Composites Part B: Engineering

DOI:https://doi.org/10.1016/j.compositesb.2025.112857· OSTI ID:2586934

^[1]; ^[1]; Rodriguez, Brittany ^[1]; ^[1]; ^[1]; ^[1]; ^[1]

Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

An image processing workflow is proposed for porosity measurement in polymer additive manufacturing. Various techniques, including global and local thresholding, region growing, and K-means clustering, were applied to microscopic images of carbon fiber reinforced acrylonitrile butadiene styrene (CF-ABS) and benchmarked for their ability to accurately measure porosity. Global methods included Otsu, minimum error, iterative, and entropy-based thresholding, while local methods included Niblack, Bernsen, Sauvola, and Bradley-Roth algorithms. Artificial uneven illumination was introduced to test local adaptive thresholds. Results showed significant differences in porosity values across methods. Otsu, region growing, and K-means clustering excelled under uniform illumination, while Sauvola and Bradley-Roth performed better with uneven illumination. Comparison with X-ray computed tomography (XCT) revealed slightly lower porosity values (2.55 %) than optimized methods (2.73–2.79 %) due to XCT's lower resolution excluding smaller pores. While XCT offers finer pore detection, it limits sample volume and underestimates porosity due to spatial variation. Validation using artificial grayscale images with 5 % porosity confirmed that Otsu, Bradley-Roth, region growing, and Sauvola algorithms produced accurate results. Although tested on a single material system, these methods can be adapted to others with optimization. In conclusion, given XCT's high computational and time costs, this study highlights suitable image processing techniques as cost-effective alternatives for porosity analysis in polymer composites.

View Accepted Manuscript (DOE)

Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Energy Efficiency Office. Advanced Materials & Manufacturing Technologies Office (AMMTO); USDOE Office of Energy Efficiency and Renewable Energy (EERE), Office of Sustainable Transportation. Vehicle Technologies Office (VTO)

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 2586934

Journal Information:: Composites Part B: Engineering, Journal Name: Composites Part B: Engineering Vol. 307; ISSN 1359-8368

Publisher:: Elsevier BVCopyright Statement

Country of Publication:: United States

Language:: English

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