Real‐time automatic crack detection method based on drone

Abstract Real‐time automated drone‐based crack detection can be used for efficient building damage assessment. This paper proposes an automated real‐time crack detection method based on a drone. Using a lightweight classification algorithm, a lightweight segmentation algorithm, a high‐precision segmentation algorithm, and a crack width measurement algorithm, the cracks are classified, roughly segmented, finely segmented, and the maximum width is extracted. A crack information‐assisted drone flight automatic control algorithm for automatic crack detection guides the drone toward the crack position. The effectiveness of the crack detection algorithm and the crack information‐assisted drone flight automatic control algorithm was tested on two different datasets, a two‐story building, and a 16‐m‐high shaking table test building. The results show that crack detection can be finished in real‐time during the flight. Using the proposed method can significantly improve the MIoU of crack edge detection and the accuracy of maximum crack width measurement under the non‐ideal shooting conditions of the actual inspection situation by automatically approaching the vicinity of the crack.