@article{20140617280861 ,
language = {English},
copyright = {Compilation and indexing terms, Copyright 2023 Elsevier Inc.},
copyright = {Compendex},
title = {Image-based retrieval of concrete crack properties for bridge inspection},
journal = {Automation in Construction},
author = {Adhikari, R.S. and Moselhi, O. and Bagchi, A.},
volume = {39},
year = {2014},
pages = {180 - 194},
issn = {09265805},
abstract = {Cracking can invite sudden failures of concrete structures. The objective of this research is to develop an integrated model based on digital image processing in developing the numerical representation of defects. The integration model consists of crack quantification, change detection, neural networks, and 3D visualization models to visualize the defects in such a way that it mimics the on-site visual inspections. The crack quantification model evaluates crack lengths based on the perimeter of the skeleton of a crack which considers the tortuosity of the crack. The change detection model is based on the Fourier Transform of digital images eliminating the need for image registration as required in the traditional. Also, the integrated model as proposed here for crack length and change detection is supported by neural networks to predict crack depth and 3D visualization of crack patterns considering crack density as a key attribute. &copy; 2013 Elsevier B.V.<br/>},
key = {Spectrum analysis},
keywords = {Concretes;Three dimensional computer graphics;Crack detection;Neural networks;Visualization;},
note = {3D Visualization;3D visualization model;Branch points;Change detection;Integrated modeling;Numerical representation;Quantification model;Visual inspection;},
URL = {http://dx.doi.org/10.1016/j.autcon.2013.06.011},
}

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