Fast crack detection method for large-size concrete surface images using percolation-based image processing
Fast crack detection method for large-size concrete surface images using percolation-based image processing
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DOI：
10.1007/s00138-009-0189-8
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发表时间：
2010-08-01
影响因子：
3.3
通讯作者：
Hashimoto, Shuji
中科院分区：
文献类型：
--
作者：
Yamaguchi, Tomoyuki;Hashimoto, Shuji
混凝土表面裂缝的检测是混凝土结构检测中最重要的一步。传统的裂缝检测方法是由有经验的人类检查员手动绘制裂缝图案来执行的；然而，这种检测方法昂贵且主观。因此，基于图像处理的裂纹自动检测技术应运而生。虽然大多数基于图像的方法都集中在裂纹检测的准确性上，但由于数字图像的大小已经增加到1000万像素，因此计算时间对于实际应用也是重要的。介绍了一种基于渗流图像处理的高效、高速的裂纹检测方法。为了减少计算时间，我们提出了终止和跳过添加过程。通过在处理过程中计算圆度来终止渗流过程。此外，可以根据相邻像素的圆度在后续像素中跳过逾渗处理。实验结果表明，该方法有效地降低了计算代价。
The detection of cracks on concrete surfaces is the most important step during the inspection of concrete structures. Conventional crack detection methods are performed by experienced human inspectors who sketch crack patterns manually; however, such detection methods are expensive and subjective. Therefore, automated crack detection techniques that utilize image processing have been proposed. Although most the image-based approaches focus on the accuracy of crack detection, the computation time is also important for practical applications because the size of digital images has increased up to 10 megapixels. We introduce an efficient and high-speed crack detection method that employs percolation-based image processing. We propose termination- and skip-added procedures to reduce the computation time. The percolation process is terminated by calculating the circularity during the processing. Moreover, percolation processing can be skipped in subsequent pixels according to the circularity of neighboring pixels. The experimental result shows that the proposed approach efficiently reduces the computation cost.