Document Type

Report

Journal/Book Title/Conference

UTC Report 01-2016

Publication Date

4-2016

Abstract

Concrete cracking is a ubiquitous phenomenon, present in all types of concrete structures. Identifying and tracking the amount and severity of cracking is paramount to evaluating the current condition and predicting the future service life of a concrete asset. Concrete cracks can indicate reinforcement corrosion, the development of spalls or changing support conditions. Therefore, monitoring cracks during the life span of concrete structures has been an effective technique to evaluate the level of safety and preparing plans for future appropriate rehabilitation.

One growing technique are unmanned inspections using Unmanned Aerial Vehicles (UAV). UAVs are drones equipped with cameras, sensors, GPS, etc. RGB images (color images in Red, Green and Blue color space) are obtained from a camera mounted on a UAV flying around the structure, to detect cracks and other defects.

Each image captured by UAV needs to be evaluated to track the crack formations. To save time, this task can be done by applying image processing techniques to automatically detect and report cracks rather than using a human to identify them. In addition, processing RGB images with sufficient information, such as the distance of camera to surface for each picture, will provide the dimension of the cracks (length and width).

The report consists of the following sections: A literature review of image processing techniques used in structural health monitoring and other fields of interest is provided in chapter 2. The Proposed method to identify cracks is demonstrated in Chapter 3. Experimental results, conclusion and future work are presented in Chapter 4. Appendix A includes the processed images using the proposed method and Appendix B includes the comparison between Talab’s method and the proposed method. In Appendix C, a “readme” file is given to run the program, and finally Appendix D shows the Matlab Code.

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