Abstract: Visual inspection by a human operator has been mostly used up till now to detect cracks in sewer pipes. In this paper, we address the problem of automated detection of such cracks. We propose a model which detects crack fractures that may occur in weak areas of a network of pipes. The model also predicts the level of dangerousness of the detected cracks among five crack levels. We evaluate our results by comparing them with those obtained by using the Canny algorithm. The accuracy percentage of this model exceeds 90% and outperforms other approaches.

Iraky Khalifa, Amal Elsayed Aboutabl and Gamal Sayed AbdelAziz Barakat, “A New Image-Based Model For Predicting Cracks In Sewer Pipes” International Journal of Advanced Computer Science and Applications(IJACSA), 4(12), 2013. http://dx.doi.org/10.14569/IJACSA.2013.041210

@article{Khalifa2013,
title = {A New Image-Based Model For Predicting Cracks In Sewer Pipes},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2013.041210},
url = {http://dx.doi.org/10.14569/IJACSA.2013.041210},
year = {2013},
publisher = {The Science and Information Organization},
volume = {4},
number = {12},
author = {Iraky Khalifa and Amal Elsayed Aboutabl and Gamal Sayed AbdelAziz Barakat}
}