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It is an essential task to inspect ground clearance of transmission lines in time. However, the weak texture of transmission lines and high complexity of the background make it difficult to balance efficiency and accuracy. To solve the problem, a trinocular vision and spatial prior based method is proposed, which is specifically designed for ground clearance measurement of transmission lines with unmanned aerial vehicles (UAVs). In this novel method, a perpendicular double-baseline trinocular vision module is applied to improve the accuracy of transmission line reconstruction. Then the spatial prior information of geometric models under different shooting attitudes is analyzed in detail, and it is adopted to determine the ground crossing points and compute ground clearance efficiently. Also, an interactive software is developed and tested in the simulation environment of UAV inspection. Experimental results verify the feasibility of the measurement method. Finally, we discuss in detail how to apply the method effectively in practice and give a set of recommended camera parameters.

Surface defect inspection for underwater structures is important. However, the inspection technologies based on passive vision cannot meet accuracy requirements. In this paper, we propose a two-stage method based on structured light images for defect detection. In the first stage, light stripes are extracted based on the analysis of hue, saturation, value (HSV) space and gray space. Then a hole-filling method is applied to ensure stripe integrity. In the second stage, depth information for all light stripes is calculated to synthesize a depth map, which is segmented for defect localization and measurement. Experimental results have verified the feasibility and effectiveness of our method.