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A statistical method for crack detection in 3D concrete images
Feb. 27, 2024, 5:47 a.m. | Vitalii Makogin, Duc Nguyen, Evgeny Spodarev
cs.CV updates on arXiv.org arxiv.org
Abstract: In practical applications, effectively segmenting cracks in large-scale computed tomography (CT) images holds significant importance for understanding the structural integrity of materials. However, classical methods and Machine Learning algorithms often incur high computational costs when dealing with the substantial size of input images. Hence, a robust algorithm is needed to pre-detect crack regions, enabling focused analysis and reducing computational overhead. The proposed approach addresses this challenge by offering a streamlined method for identifying crack regions …
abstract algorithms applications arxiv computational concrete costs cs.cv detection images importance integrity machine machine learning machine learning algorithms materials practical scale stat.ap statistical statistical method type understanding
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