Summary
In this paper a new method of cracks detection is introduced. The proposed algorithm is applied to detect the cracks in the pavement image. Local minimum and linear relation between them was proposed. The proposed method is classify into two stages: linear local minimum and verification of detecting of pavement cracking. This method is fast although is complex. Additionally, the proposed method eliminates slight and strong variations like irregularly illuminated conditions, shading and road signs painted on pavement surface.
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References
ASTM Standard practice for roads and parking lots. Pavement Condition Index surveys ASTM designation D 6433-99 (1999)
Austroads: A Guide to the Visual assessment of pavement condition, Sydney (1987)
Chan, P., Rao, L.L., Lytton, L.R.: Development of Image Algorithms for Automated Pavement Distress Evaluation System. FHWA Report TX-92/1189-2F. TX: Texas Transportation Institute, Texas A and M University (1992)
FHWA Distress identification manual for the long-term pavement performance project. FHWA-RD-03-031 (2003)
GDDP - BSSD System oceny stanu nawierzchni SOSN - wytyczne stosowania, Warszawa (2002)
Maode, Y., Shaobo, B., Kun, X., Yuyao, H.: Pavement Crack Detection and Analysis for High-grade Highway. In: Eighth International Conference on Electronic Measurement and Instruments, ICEMI (2007)
Marchewka, A., Miciak, M.: Subtract-filtering Pre-processing for Cracks Detection. In: Choraś, R.S., Zabłudowski, A. (eds.) Image Processing & Communications Challenges, pp. 225–230. Academy Publishing House EXIT, Warsaw (2009)
Marchewka, A.: Location Of Pavement Surface Distress Using Digital Processing - A Survey. Image Processing & Communications (2009)
Subirats, P., Fabre, O., Dumoulin, J., Legeay, V., Barba, D.: A Combined Wavelet-Based Image Processing Method for Emergent Crack Detection on Pavement Surface Images. In: EUSIPCO, Vienna, Austria (2004)
Subirats, P., Dumoulin, J., Legeay, V., Barba, D.: Automation of Pavement Surface Crack Detection Using The Continuous Wavelet Transform. In: ICIP, pp. 3037–3040 (2006)
Sy, N.T., Avila, M., Begot, S., Bardet, J.C.: Detection of Defects in Road Surface by a Vision System. In: The 14th IEEE Mediterranean, Electrotechnical Conference, MELECON 2008, pp. 847–851 (2008)
Teomete, E., Amin, V.R., Ceylan, H., Smadi, O.: Digital Image Processing for Pavement Distress Analyses. In: Proceedings of the 2005 Mid-Continent Transportation Research Symposium, Ames, Iowa (2005)
Yusuke, F., Yoshihiro, M., Yoshihiko, H.: A Method for Crack Detection on a Concrete Structure. In: ICPR 2006: Proceedings of the 18th International Conference on Pattern Recognition, pp. 901–904. IEEE Computer Society, Washington (2006)
Xu, B., Huang, Y.: Automatic Inspection of Pavement Cracking Distress. Journal of Electronic Imaging 15 (2006)
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Marchewka, A. (2010). Crack Detection on Asphalt Surface Image Using Local Minimum Analysis. In: Choraś, R.S. (eds) Image Processing and Communications Challenges 2. Advances in Intelligent and Soft Computing, vol 84. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16295-4_41
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DOI: https://doi.org/10.1007/978-3-642-16295-4_41
Publisher Name: Springer, Berlin, Heidelberg
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