To improve the robustness of concrete crack detection in complex environments that feature non-uniform illumination,low contrast, and stain noise, such as roads, bridges, I present a systematic approach for automatic crack detection onUAV images for monitoring concrete facilities such as buildings and civil structures. A two-step process was applied.First, a deep learning processing technique for region detection of cracks, and then crack detection based on the imageprocessing and region properties. I applied transfer learning approach to use a pre-trained network in order to identifycracks. I used pixel value based binarization of image data with an edge-preserving filter, which reduced noise in theregion. Experimental results from UAV images showed that our approach has a good potential to be applied to concretecrack detection.
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