The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.
Automatic Road Pavement Assessment with Image Processing: Review and Comparison
Open accessAbstract
In the field of noninvasive sensing techniques for civil infrastructures monitoring, this paper addresses the problem of crack detection, in the surface of the French national roads, by automatic analysis of optical images. The first contribution is a state of the art of the image-processing tools applied to civil engineering. The second contribution is about fine-defect detection in pavement surface. The approach is based on a multi-scale extraction and a Markovian segmentation. Third, an evaluation and comparison protocol which has been designed for evaluating this difficult task—the road pavement crack detection—is introduced. Finally, the proposed method is validated, analysed, and compared to a detection approach based on morphological tools.
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Citations
Cites
Detection of blood vessels in retinal images using two-dimensional matched filters
Chaudhuri, S., Chatterjee, S., Katz, N., Nelson, M., & Goldbaum, M. (1989) · IEEE Transactions on Medical Imaging · doi:10.1109/42.34715 · Cited by 1,668
Analysis of Edge-Detection Techniques for Crack Identification in Bridges
Abdel-Qader, I., Abudayyeh, O., & Kelly, M. E. (2003) · Journal of Computing in Civil Engineering · doi:10.1061/(asce)0887-3801(2003)17:4(255 · Cited by 892
An active testing model for tracking roads in satellite images
Geman, D., & Jedynak, B. (1996) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.476006 · Cited by 498
Automatic road crack segmentation using entropy and image dynamic thresholding
Oliveira, H. J. M., & Correia, P. L. (2009) · Cited by 315
Automatic inspection of pavement cracking distress
Huang, Y., & Xu, B. (2006) · Journal of Electronic Imaging · doi:10.1117/1.2177650 · Cited by 214
Novel Approach to Pavement Cracking Detection Based on Fuzzy Set Theory
Cheng, H. D., Chen, J.-R., Glazier, C., & Hu, Y. G. (1999) · Journal of Computing in Civil Engineering · doi:10.1061/(asce)0887-3801(1999)13:4(270 · Cited by 196
A neural network-based methodology for pavement crack detection and classification
Kaseko, M. S., & Ritchie, S. G. (1993) · Transportation Research Part C Emerging Technologies · doi:10.1016/0968-090x(93)90002-w · Cited by 175
A robust approach for automatic detection and segmentation of cracks in underground pipeline images
Iyer, S., & Sinha, S. K. (2005) · Image and Vision Computing · doi:10.1016/j.imavis.2005.05.017 · Cited by 162
Wavelet-Based Pavement Distress Image Edge Detection with À Trous Algorithm
Wang, K. C. P., Li, Q., & Gong, W. (2007) · Transportation Research Record Journal of the Transportation Research Board · doi:10.3141/2024-09 · Cited by 145
Primitive‐Based Classification of Pavement Cracking Images
Koutsopoulos, H. N., & Downey, A. B. (1993) · Journal of Transportation Engineering · doi:10.1061/(asce)0733-947x(1993)119:3(402 · Cited by 96
Cited by
DeepCrack: A deep hierarchical feature learning architecture for crack segmentation
Liu, Y., Yao, J., Lu, X., Xie, R., & Li, L. (2019) · Neurocomputing · doi:10.1016/j.neucom.2019.01.036 · Cited by 1,158
Automatic Road Crack Detection and Characterization
Oliveira, H., & Correia, P. L. (2013) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2012.2208630 · Cited by 537
Amhaz, R., Chambon, S., Idier, J., & Baltazart, V. (2016) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2015.2477675 · Cited by 507
Self-citationDais, D., Bal, İ. E., Smyrou, E., & Sarhosis, V. (2021) · Automation in Construction · doi:10.1016/j.autcon.2021.103606 · Cited by 429
Kheradmandi, N., & Mehranfar, V. (2022) · Construction and Building Materials · doi:10.1016/j.conbuildmat.2021.126162 · Cited by 426
Metadata
- Authors
- Chambon, S., & Moliard, J.-M.
- Venue
- International Journal of Geophysics
- Publisher
- Hindawi Limited
- Published
- 2011
- Volume
- 2011
- Pages
- 1-20
- ISSN
- 1687-885X (ISSN-L)
- 1687-8868
- OpenAlex
- W1963782251
- Cited by
- 276
- References
- 27
- FWCI
- 18.49
- Type
- journal article
- Language
- en
- Open access
- gold
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- Chambon, S., & Moliard, J.-M. (2011). Automatic Road Pavement Assessment with Image Processing: Review and Comparison. International Journal of Geophysics. https://doi.org/10.1155/2011/989354
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
