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Computers and Concrete Volume 21, Number 6, June 2018 , pages 727-739 DOI: https://doi.org/10.12989/cac.2018.21.6.727 |
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Morphological segmentation based on edge detection-II for automatic concrete crack measurement |
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Tung-Ching Su and Ming-Der Yang
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| Abstract | ||
| Crack is the most common typical feature of concrete deterioration, so routine monitoring and health assessment become essential for identifying failures and to set up an appropriate rehabilitation strategy in order to extend the service life of concrete structures. At present, image segmentation algorithms have been applied to crack analysis based on inspection images of concrete structures. The results of crack segmentation offering crack information, including length, width, and area is helpful to assist inspectors in surface inspection of concrete structures. This study proposed an algorithm of image segmentation enhancement, named morphological segmentation based on edge detection-II (MSED-II), to concrete crack segmentation. Several concrete pavement and building surfaces were imaged as the study materials. In addition, morphological operations followed by cross-curvature evaluation (CCE), an image segmentation technique of linear patterns, were also tested to evaluate their performance in concrete crack segmentation. The result indicates that MSED-II compared to CCE can lead to better quality of concrete crack segmentation. The least area, length, and width measurement errors of the concrete cracks are 5.68%, 0.23%, and 0.00%, respectively, that proves MSED-II effective for automatic measurement of concrete cracks. | ||
| Key Words | ||
| concrete crack; aging concrete; cracking; morphological segmentation; edge detection | ||
| Address | ||
| Tung-Ching Su: Department of Civil Engineering and Engineering Management, National Quemoy University, Kinmen, Taiwan Ming-Der Yang: Department of Civil Engineering, and Innovation and Development Center of Sustainable Agriculture, National Chung Hsing University, Taichung City, Taiwan | ||