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• W2883600644 abstract "Monitoring the instantaneous and changing concrete surface condition is paramount to cost-effectively managing tunnel assets. In practice, detecting cracks efficiently and accurately is a very challenging task due to concrete blebs, stains, and illumination over the concrete surface. Unclear and tiny cracks cannot be detected effectively. In this paper, we proposed an ultra-efficient crack detection algorithm (CrackHHP) and an improved pre-extraction and second percolation process based on the percolation model to address these issues. Our contributions are shown as follows: 1) apply the overlapping grids and weight-based, redefined pixel value to obtain the candidate dark pixel image while preserving the cracks. 2) introduce the second percolation processing to generate a high-accuracy crack detection algorithm, which can connect the tiny fractures and detect the tiny cracks. 3) construct a high-efficiency and high-accuracy crack detection algorithm combining the improved pre-extraction and the second percolation process. The experimental results demonstrate that CrackHHP can significantly improve the efficiency and accuracy of crack detection." @default.
• W2883600644 created "2018-08-03" @default.
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• W2883600644 date "2018-07-26" @default.
• W2883600644 modified "2023-09-23" @default.
• W2883600644 title "Concrete surface crack detection with the improved pre-extraction and the second percolation processing methods" @default.
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• W2883600644 doi "https://doi.org/10.1371/journal.pone.0201109" @default.
• W2883600644 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6062087" @default.
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