The application of Unmanned Aerial Systems (UAS) will likely influence the civil engineering industry in the near future. UAS can quickly collect image data, which can be used to identify structural damage. In particular, bridge decks are of interest because they provide a driving surface for vehicles and protect bridges from the environment. Damage on a bridge deck can take the form of delaminations and surface cracks which can be a good indication of deck deterioration. Delaminations can be identified by their different heat transfer characteristics using an infrared camera and surface cracks can be observed with high resolution color images. Image processing techniques and computer vision algorithms can be applied to detect areas of interest from UAS imagery as well as to direct inspectors to targeted locations for further investigation using other contact techniques such as impact echo or chain drag. To demonstrate such capabilities, a simulated bridge deck with internal and external manufactured defects was used in this study. The locations of the defects were unknown to the authors before the flight. A post processing algorithm was developed to leverage both color and infrared aerial images and display global information of local simulated damage.
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