Bridges are mega structures that have been utilized and built for millennia. These structures are highly effective in achieving transportation and commute between two highly inaccessible destinations easily. Bridges are also highly effective in reducing traffic was by allowing the use of an alternate path for the traffic flow to be resumed. This makes them highly versatile and extremely effective in various scenarios. But as with any constructed structures, these bridges need to be evaluated for their structural integrity and surveyed for any flaws or cracks that have been emerged over time. This is usually done manually by a civil engineer which is a time consuming process and can also introduce human error. Therefore to improve this procedure and number of related works have been analyzed extensively to achieve bridge crack detection through image processing methodologies. An effective approach has been envisioned through the use of convolutional neural networks and decision tree techniques to achieve bridge crack detection which will be further elaborated in the next edition of this research article.
by Ketan Ovhal | Ruturaj Lokhande | Omkar Kamble | Prathamesh Nanaware | Samarsingh Jadhav "An In-depth Review on Bridge Crack Detection Approaches"
Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021,
URL: https://www.ijtsrd.compapers/ijtsrd42401.pdf
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