Concrete surface crack detection with the improved pre-extraction and the second percolation processing methods

Zhong Qu, Fang-Rong Ju, Yang Guo, Ling Bai and Kuo Chen

PLOS ONE, 2018, vol. 13, issue 7, 1-14

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.

Date: 2018
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0201109

DOI: 10.1371/journal.pone.0201109

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