Automatic road crack detection and characterization

IEEE Transactions on Intelligent Transportation Systems

Volumn 14, Issue 1, 2013, Pages 155-168

  Oliveira, Henrique ^a,b   Correia, Paulo Lobato ^a  

^a INSTITUTO DE TELECOMUNICAÇÕES   (Portugal)

^b INSTITUTO POLITÉCNICO DE BEJA   (Portugal)

Author keywords

Clustering; crack characterization; crack severity level; road crack detection; segmentation; unsupervised learning

Indexed keywords

AUTOMATIC DETECTION; CLASSIFICATION SYSTEM; CLUSTERING; CRACK CHARACTERIZATION; CRACK SEVERITY; FLEXIBLE PAVEMENTS; QUANTITATIVE EVALUATION; UNSUPERVISED TRAINING;

CHARACTERIZATION; CRACK DETECTION; IMAGE SEGMENTATION; PAVEMENTS; SURVEYS; UNSUPERVISED LEARNING;

CRACKS;

EID: 84879315708     PISSN: 15249050     EISSN: None     Source Type: Journal    
DOI: 10.1109/TITS.2012.2208630     Document Type: Article

References (37)

1. S. Cafiso, A. Graziano, and S. Battiato, "Evaluation of pavement surface distress using digital image collection and analysis," in Proc. 7th Int. Congr. Adv. Civil Eng., Istanbul, Turkey, 2006.
2. Y. Huang and B. Xu, "Automatic inspection of pavement cracking distress," J. Electron. Imag., vol. 15, no. 1, pp. 013017-1-013017-6, Feb. 2006.
3. H. Cheng and M. Miyojim, "Automatic pavement distress detection system," Inf. Sci., vol. 108, no. 1-4, pp. 219-240, Jul. 1998. (Pubitemid 128383838)
4. J. Zhang, F. Wang, K. Wang, W. Lin, X. Xu, and C. Chen, "Data-driven intelligent transportation systems: A survey," IEEE Trans. Intell. Transp. Syst., vol. 12, no. 4, pp. 1624-1639, Dec. 2011.
5. H. Cheng and S. Hsu, "Intelligent highway traffic surveillance with selfdiagnosis abilities," IEEE Trans. Intell. Transp. Syst., vol. 12, no. 4, pp. 1462-1472, Dec. 2011.
6. H. Zhang and Q. Wang, "Use of artificial living system for pavement distress survey," in Proc. 30th Annu. Conf. IEEE Ind. Electron. Soc., Busan, Korea, 2004, pp. 2486-2490. (Pubitemid 40845456)
7. Catalogo de Degradacoes dos Pavimentos Rodoviarios Flexiveis-2nd ver., JAE, Ex-Junta Autonoma das Estradas, Almada, Portugal, , 1997.
8. S. Chambon, P. Subirats, and J. Dumoulin, "Introduction of a wavelet transform based on 2D matched filter in a Markov random field for fine structure extraction: Application on road crack detection," in Proc. IST/SPIE Electron. Imag. Sci. Technol., San Jose, CA, 2009, pp. 72510A-1-72510A-12.
9. Y. Sun, E. Salari, and E. Chou, "Automated pavement distress detection using advanced image processing techniques," in Proc. IEEE Int. Conf. Electro/Inf. Technol., Windsor, ON, Canada, 2009, pp. 373-377.
10. C. Ma, W. Wang, C. Zhao, F. Di, and Z. Zhu, "Pavement cracks detection based on FDWT," in Proc. IEEE Int. Conf. CiSE, Wuhan, China, 2009, pp. 1-4.
11. A. Ayenu-Prah and N. Attoh-Okine, "Evaluating pavement cracks with bidimensional empirical mode decomposition," EURASIP J. Adv. Signal Process., vol. 2008, no. 1, pp. 861701-1-861701-7, 2008.
12. P. Ekdahl, Routine Measurements of Pavement Surface Cracks, Ramboll RST, Malmo, Sweden. [Online]. Available: http://carbon.videolectures. net/2008/contrib/surf08-portoroz/ekdahl-rmopsc/surf08-ekdahl-rmopsc-01.pdf
13. C. Ma, C. Zaho, and Y. Hou, "Pavement distress detection based on nonsubsampled contourlet transform," in Proc. IEEE Int. CSSE, Wuhan, China, 2008, pp. 28-31.
14. Q. Li and X. Liu, "Novel approach to pavement image segmentation based on neigbhboring difference histogram method," in Proc. IEEE CISP, Sanya, China, 2008, pp. 792-796.
15. F. Liu, G. Xu, Y. Yang, X. Niu, and Y. Pan, "Novel approach to pavement cracking automatic detection based on segment extending," in Proc. IEEE Int. Symp. KAM, Wuhan, China, 2008, pp. 610-614.
16. N. Otsu, "Threshold selection method from gray-level histograms," IEEE Trans. Syst., Man, Cybern., vol. SMC-9, no. 1, pp. 62-66, Jan. 1979. (Pubitemid 9413341)
17. J. Kapur, P. Sahoo, and A. Wogn, "A new method for gray-level picture thresholding using entropy of the histogram," Comput. Vis., Graph., Imag. Process., vol. 29, no. 3, pp. 273-285, Mar. 1985. (Pubitemid 15510905)
18. W.Wei and B. Liu, "Automatic road crack image preprocessing for detection and identification," in Proc. IEEE 2nd ICINIS, Tianjin, China, 2009, pp. 319-322.
19. Y. Huang and Y. Tsai, "Enhanced pavement distress segmentation algorithm using dynamic programming and connected component analysis," in Proc. 90th Meeting Transp. Res. Board, 2011.
20. T. Nguyen, M. Avila, and B. Stephane, "Automatic detection and classification of defect on road pavement using anisotropy measure," in Proc. 17th EUSIPCO, Glasgow, U.K., 2009, pp. 617-621.
21. B. Lee and H. Lee, "Position-invariant neural network for digital pavement crack analysis," Comput.-Aided Civil Infrastruct. Eng., vol. 19, no. 2, pp. 105-118, Mar. 2004. (Pubitemid 38300822)
22. S. Cambon and J. Moliard, "Automatic road pavement assessment with image processing: Review and comparison," Int. J. Geophys., vol. 2011, pp. 989354-1-989354-20, Jun. 2011.
23. H. Oliveira and P. Correia, "Supervised crack detection and classification in images of road pavement flexible surfaces," in Recent Advances in Signal Processing, A. A. Zaher, Ed. Vienna, Austria: I-Tech, 2009, pp. 159-184.
24. D. Tax, Dec. 2009. [Online]. Available: http://prlab.tudelft.nl/david- tax/dd-tools.html
25. R. Dwin, D. Ridder, P. Juszczak, C. Lai, P. Paclik, E. Pekalska, and D. Tax, PRTools-A Matlab toolbox for pattern recognition, PRTools, Delft, The Netherlands. [Online]. Available: http://www.prtools.org
26. D. Tax, "One-class classification: Concept-learning in the absence of counter-examples," Delft Univ. Technol., Delft, The Netherlands, 2001.
27. H. Oliveira and P. Correia, "Identifying and retrieving distress images from road pavement surveys," in Proc. 15th IEEE ICIP, San Diego, CA, 2008, pp. 57-60.
28. A. Wright, Developing the Automatic Measurement of Surface Condition on Local Roads, Slovenia, 2008. [Online]. Available: http://carbon.videolectures. net/2008/contrib/surf08-portoroz/wright-dtamos/surf08-wright-dtamos-01.pdf
29. C. Arcelli and G. Baja, "Skeletons of planar patterns," in Topological Algorithms for Digital Image Processing, T. Kong and A. Rosenfeld, Eds. New York: Elsevier, 1996, pp. 99-144. (Pubitemid 126099353)
30. A. Sanz, Pavement Surface Defects: Classification and Quantification Over a Road Network, 2008. [Online]. Available: http://carbon. videolectures.net/ 2008/contrib/surf08-portoroz/amirola-psdca/surf08-amirola-psdca-01.pdf
31. Laser Road Imaging System (LRIS), INO, Quebec City, QC, Canada, Jan. 2012. [Online]. Available: http://www.ino.ca/en-ca/achievements/description/ project-p/laser-road-imaging.html
32. Q. Pan, L. Zhang, G. Dai, and H. Zhang, "Two denoising methods by wavelet transform," IEEE Trans. Image Process., vol. 47, no. 12, pp. 3401-3406, Dec. 1999. (Pubitemid 30531532)
33. L. Zhang and P. Bao, "Denoising by spatial correlation thresholding," IEEE Trans. Circuits Syst. Video Technol., vol. 13, no. 6, pp. 535-538, Jun. 2003.
34. A. Suyash and R. Whitaker, "Unsupervised, information-theoretic, adaptative image filtering for image restoration," IEEE Trans. Pattern Anal. Mach. Intell., vol. 28, no. 3, pp. 364-376, Mar. 2006. (Pubitemid 43159633)
35. S. Kim and R. Park, "Fast local motion-compensation algorithm for video sequences with brightness variantions," IEEE Trans. Circuits Syst. Video Technol., vol. 13, no. 4, pp. 289-299, Apr. 2003.
36. Identification Manual for the Long-Term Pavement Performance Program, Fed. Hwy. Admin., U.S. Dept. Transp., Washington, DC, , Jan. 2012.
37. R. Elunai, V. Chandran, and E. Gallagher, "Asphalt concrete surfaces macrotexture determination from still images," IEEE Trans. Intell. Transp. Syst., vol. 12, no. 3, pp. 857-869, Sep. 2011.