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Proceedings Paper

Artificial intelligence and signal processing for infrastructure assessment
Author(s): Khaled Assaleh; Tamer Shanableh; Sherif Yehia
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Paper Abstract

The Ground Penetrating Radar (GPR) is being recognized as an effective nondestructive evaluation technique to improve the inspection process. However, data interpretation and complexity of the results impose some limitations on the practicality of using this technique. This is mainly due to the need of a trained experienced person to interpret images obtained by the GPR system. In this paper, an algorithm to classify and assess the condition of infrastructures utilizing image processing and pattern recognition techniques is discussed. Features extracted form a dataset of images of defected and healthy slabs are used to train a computer vision based system while another dataset is used to evaluate the proposed algorithm. Initial results show that the proposed algorithm is able to detect the existence of defects with about 77% success rate.

Paper Details

Date Published: 1 April 2015
PDF: 9 pages
Proc. SPIE 9437, Structural Health Monitoring and Inspection of Advanced Materials, Aerospace, and Civil Infrastructure 2015, 94372O (1 April 2015); doi: 10.1117/12.2179920
Show Author Affiliations
Khaled Assaleh, American Univ. of Sharjah (United Arab Emirates)
Tamer Shanableh, American Univ. of Sharjah (United Arab Emirates)
Sherif Yehia, American Univ. of Sharjah (United Arab Emirates)


Published in SPIE Proceedings Vol. 9437:
Structural Health Monitoring and Inspection of Advanced Materials, Aerospace, and Civil Infrastructure 2015
Peter J. Shull, Editor(s)

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