Научная визуализация, 2026, том 18, номер 1, страницы 49 - 61, DOI: 10.26583/sv.18.1.05
Enhanced Crack Width and Depth Measurement through Binary Image Processing and Geometric Analysis
Авторы: Kavita Bodke1,A, Sunil Bhirud2,B, Keshav Kashinath Sangle3,A
A Veermata Jijabai Technological Institute, Mumbai, India
B COEP Technological University, Pune, India
1 ORCID: 0000-0003-4498-5393, kvbodke_p21@ce.vjti.ac.in
2 ORCID: 0000-0002-9100-6437
3 ORCID: 0000-0003-0618-7526
Аннотация
This paper presents a novel, image-based approach for automatically quantifying structural crack width and depth in concrete using binary image processing techniques. Concrete cracks are critical indicators of potential structural failure, and traditional manual inspection methods are often time-consuming, unsafe, and prone to inaccuracies. The proposed method automates crack detection by converting RGB images of concrete surfaces into binary images, isolating the cracks, and measuring their width using the Euclidean distance formula. The depth of the cracks is then estimated using trigonometric relationships based on the measured crack width and viewing angles (30°, 45°, and 60°). This lightweight, cost-effective approach provides a practical alternative to more complex machine learning-based detection methods, making it ideal for real-time infrastructure health monitoring. The results highlight the effectiveness of this technique in accurately measuring crack width and depth across multiple angles, providing critical data for infrastructure health monitoring.
Ключевые слова: Crack width, crack depth, Euclidean distance, binary image processing, trigonometry, structural health monitoring.
