Crack assessment is an essential process in the maintenance of concrete structures.\nIn general, concrete cracks are inspected by manual visual observation of the surface, which is\nintrinsically subjective as it depends on the experience of inspectors. Further, it is time-consuming,\nexpensive, and often unsafe when inaccessible structural members are to be assessed. Unmanned\naerial vehicle (UAV) technologies combined with digital image processing have recently been\napplied to crack assessment to overcome the drawbacks of manual visual inspection. However,\nidentification of crack information in terms of width and length has not been fully explored in\nthe UAV-based applications, because of the absence of distance measurement and tailored image\nprocessing. This paper presents a crack identification strategy that combines hybrid image processing\nwith UAV technology. Equipped with a camera, an ultrasonic displacement sensor, and aWiFi module,\nthe system provides the image of cracks and the associated working distance from a target structure\non demand. The obtained information is subsequently processed by hybrid image binarization\nto estimate the crack width accurately while minimizing the loss of the crack length information.\nThe proposed system has shown to successfully measure cracks thicker than 0.1 mm with the\nmaximum length estimation error of 7.3%.
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