An image processing approach for fatigue crack identification in cellulose acetate replicas

• Published in: Engineering failure analysis 2024-10, Vol.164, p.108663, Article 108663
• Main Authors: Pałczyński, Krzysztof, Seyda, Jan, Skibicki, Dariusz, Pejkowski, Łukasz, Macek, Wojciech
• Format: Article
• Language: English
• Subjects: Cellulose acetate replicas; Fatigue crack detection; Image processing
• ISSN: 1350-6307
• DOI: 10.1016/j.engfailanal.2024.108663

•Extracting accurate data from cellulose replicas poses distortions and artifact.•Handcrafted features address limited data challenges, proving algorithm robustness.•Capable of identifying cracks as small as 30 μm, overcoming replication artifacts.•Captures orientation, length, and growth stages, crucial for understanding fatigue mechanisms. The cellulose acetate replication technique is an important method for studying material fatigue. However, extracting accurate information from pictures of cellulose replicas poses challenges because of distortions and numerous artifacts. This paper presents an image processing procedure for effective fatigue crack identification in plastic replicas. The approach employs thresholding, adaptive Gaussian thresholding, and Otsu binarization to convert gray-scale images into binary ones, enhancing crack visibility. Morphological operations refine object shapes, and Connected Components Analysis facilitates crack identification. Despite limited data, the handcrafted feature extraction algorithm proves robust, addressing challenges. The algorithm shows efficacy in detecting cracks as small as 30 μm, even in the presence of cellulose replication artifacts. The results highlight ability to capture significant cracks’ orientation, length, and growth stages, essential for understanding fatigue mechanisms. Analysis of results, especially evaluation metrics encompassing false positives and false negatives, provides a comprehensive understanding of the algorithm’s strengths and limitations. The proposed tool is available on GitHub.