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Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.
A New Image-Based Model For Predicting Cracks In Sewer Pipes
Digital Object Identifier (DOI) : 10.14569/IJACSA.2013.041210
Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 4 Issue 12, 2013.
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.
Keywords: Visual inspection; Sewer pipes; Canny algorithm; Crack detection
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}
}
