A new technique for automatic detection and parameters estimation of pavement crack

IMETI 2011 - 4th International Multi-Conference on Engineering and Technological Innovation, Proceedings

Volumn 2, Issue , 2011, Pages 11-16

  Moussa, Ghada ^a   Hussain, Khaled ^b  

^a Assiut University   (Egypt)

^b Assiut University   (Egypt)

Author keywords

Crack detection; Flexible pavement; Image processing; Support vector machine

Indexed keywords

FLEXIBLE PAVEMENTS; IMAGE PROCESSING TECHNIQUE; MACHINE LEARNING METHODS; PARAMETERS ESTIMATION; PAVEMENT DETERIORATION; PAVEMENT MAINTENANCE; PAVEMENT MANAGEMENT SYSTEMS; PAVEMENT SERVICE LIFE;

CONCRETE PAVEMENTS; CRACK DETECTION; DECISION MAKING; IMAGE PROCESSING; LEARNING SYSTEMS; MAINTENANCE; ROADS AND STREETS; SUPPORT VECTOR MACHINES;

CRACKS;

EID: 84890885560     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (30)

1. J.S Miller and W.Y. Bellinger, Distress Identification Manual for Long-Term Performance Program (Fourth Revised Edition), Office of Infrastructure Research and Development, Federal Highway Administration, Report No. FHWA-RD-03-031, 2003.
2. R.J. Dilger, American Transportation Policy. West Virginia University, Department of Political Science. Westport, CT: Praeger Publishers, 2003.
3. A. Ouyang, C. Luo and C. Zhou, "Surface Distresses Detection of Pavement Based on Digital Image Processing, Advances in Information and Communication Technology, Vol. 347, 2011, pp. 368-375.
4. J. Kim, Development of a Low-Cost Video Imaging System for Pavement Evaluation, Ph.D. Thesis, Oregon State University. Oregon, United States, 1998.
5. H.D. Cheng and M. Miyojim, "Automatic Pavement Distress Detection System", Journal of Information Sciences, ELSEVIER, Vol. 108, No. 1, 1998, pp. 219-240.
6. K.A. Abaza, S.A. Ashur, and I.A. Al-Khatib. "Integrated Pavement Management System with a Markovian Prediction Model," Journal of Transp. Eng., Vol. 130, No. 1, 2004, pp. 24-33.
7. K. McGhee. Automated Pavement Distress Collection Techniques, NCHRP Synthesis 334, National Cooperative Highway Research Program (NCHRP), USA., 2004.
8. L. Li, P. Chan, and R.L. Lytton, "Detection of Thin Cracks on Noisy Pavement Images", Transp. Res. Record, No. 1311, pp. 131-135, 1991.
9. K. Wang, "Design and Implementations of Automated Systems for Pavement Surface Distress Survey", Journal of Infrastructure Systems, ASCE. Vol. 6, 2000.
10. Y. Hu, C.X. Zhao, "A Local Binary Pattern Based Methods for Pavement Crack Detection", Journal of Pattern Recognition Research, Vol. 5, No. 1, 2010, pp. 140-147.
11. H.D. Cheng, J.R. Chen, C. Glazier, C. and Y. G. Hu, "Novel Approach to Pavement Cracking Detection Based on Fuzzy Set Theory", Journal of Computing in Civil Eng., Vol. 13, No. 4, 1999. pp. 270-280.
12. P. Delagnes and D. Barba, "A markov random field for rectilinear structure extraction in pavement distress image analysis," in Proceedings of IEEE International Conference on Image Processing (ICIP '95), Vol. 1, pp. 446-449. Washington, DC, USA, October 1995.
13. 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 IS&T/SPIE Electronic Imaging, Image Processing: Machine Vision Applications II, San Jose, USA, 2009.
14. th Annual Conference of IEEE, Pusan. Korea, Nov. 2004, pp. 2486-2490.
15. J. Chou, W.A. O'Neill, and H.D. Cheng, "Pavement Distress Classification Using Neural Networks", Systems, Man, Cyberneticsl, IEEE. 1994, pp. 397-40.
16. H.D. Cheng, J.L. Wang, Y.G. Hu, C. Glazier. H.J. Shi. and X.W. Chen, "Novel Approach to Pavement Cracking Detection Based on Neural Network", Transp. Res. Record, No. 1764, pp. 119-127, 2001.
17. B.J. Lee, and H.D. Lee, "Position-invariant neural network for digital pavement crack analysis", Computer-Aided Civil and Infrastructure Engineering, vol. 19, no. 2, 2004, pp. 105-118.
18. H. Lee, and H. Oshima, "New crack-imaging procedure using spatial autocorrelation function" ASCE Journal of Transp. Eng., Vol. 120, No. 2, 1994, pp. 206-228.
19. H. Oliveira, and P.L. Correia, Supervised Crack Detection and Classification in Images of Road Pavement Flexible Surfaces, Chapter in Recent Advances in Signal Processing, Austria, 2009.
20. G. Younes, C. Hadda, and Z. Djellou, "Supervised Learning and Automatic Recognition of Asphalt Pavement Deteriorations". MASAUM Journal of Basic and Applied Sciences, Vol. 1, No. 2, September 2009, pp. 254-259.
21. Y. Boykov, and M. Jolly, "Interactive Graph Cuts for Optimal Boundary & Region Segmentation of Objects in N-D Images", in Proceedings of Eighth IEEE International Conference on Computer Vision (ICCV), Vol. I, 2001, pp. 105-112.
22. Y. Li, J. Sun, CK. Tang, and H. Y. Shum. "Lazy Snapping", SIGGRAPH04, April 2004.
23. L. Vincent, and P. Soille, "Watersheds in digital spaces: an efficient algorithm based on immersion simulations". IEEE Transactions on Pattern Analysis and Machine Intelligence, 1991, pp. 583-598.
24. Y. Boykov, and V. Kolmogorov, "An Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in Vision", Energy Minimization Methods in Computer Vision & Pattern Recognition, 2001.
25. A.D. Sahibsingh, J.B. Kenneth, & B.M. Robert, "Aircraft Identification by Moment Invariants", IEEE Transactions on Computers, Vol. 26 No. 1, 1977, pp. 39-45.
26. C.H. Lampert, "Kernel Methods in Computer Vision", Foundations and Trends in Computer Graphics & Vision, Vol. 4, No. 3, 2009, pp. 193-285.
27. V. Vapnik, The Nature of Statistical Learning Theory, New York: Springer-Verlag, 1995.
28. A. Amarasiri, M. Gunaratne, and S. Sarkar, "Modeling of Crack Depths in Digital Images of Concrete Pavements using Optical Reflection Properties", Journal of Transp. Eng., Vol. 136, No. 6, June 2010, pp. 489-499.
29. M.A. Fischler, and R.C. Bolles, '"Random Sample Consensus: A Paradigm for Model Fitting With Applications to Image Analysis and Automated Cartography", Communications of the ACM, Vol. 24, No. 6, 1981, pp. 381-395.
30. L. Lam, S.W. Lee, and C.Y. Suen, "Thinning Methodologies - A Comprehensive Survey", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 14, No. 9, 1992, pp. 869-885.