Fractals and independent component analysis for defect detection in bridge decks

Abstract

We present in this paper a framework for the automatic detection and localization of defects inside bridge decks. Using Ground-Penetrating Radar (GPR) raw scans, this framework is composed of a feature extraction algorithm using fractals to detect defective regions and a deconvolution algorithm using banded-independent component analysis (ICA) to reduce overlapping between reflections and to estimate the radar waves travel time and depth of defects. Results indicate that the defects' estimated horizontal location and depth falling within 2cm (76.92% accuracy) and 1cm (84.62% accuracy) from their actual values. Copyright © 2011 Ikhlas Abdel-Qader et al.