Defect detection method and device for facilities on both sides of road
A defect detection and facility technology, applied in image analysis, image enhancement, instruments, etc., can solve problems such as poor performance and reduce highway traffic efficiency, and achieve the effects of improving detection efficiency, realizing automatic detection, and ensuring traffic efficiency
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Embodiment 1
[0043] like figure 1 and figure 2 As shown, the present invention discloses a defect detection method for facilities on both sides of a road, including:
[0044] In step S1, images of facilities on both sides of the road are acquired, and the images are input into the trained image segmentation network to obtain a guardrail mask and a visor mask;
[0045] Step S2, according to the obtained guardrail mask and shading plate mask, determine whether the guardrail and the shading plate have defects, specifically:
[0046] Traverse the guardrail mask along the column direction and collect candidate edge points, select the interior points of the guardrail boundary by random sampling consensus algorithm, and fit the boundary line by the least square method; judge whether there is existence according to the distance from all candidate edge points to the fitting boundary Defect, the candidate edge point is the pixel point of the mask edge;
[0047] Perform edge detection on the shad...
Embodiment 2
[0071] refer to Image 6 , the present invention also discloses a defect detection device for facilities on both sides of the road, comprising: an image acquisition module 101, an image segmentation module 102, a defect analysis module 103 and a result output module 104;
[0072] The image acquisition module 101 is used to acquire images of facilities on both sides of the road;
[0073] The image segmentation module 102 is used to input the acquired image into the trained image segmentation network to obtain a guardrail mask and a visor mask;
[0074] The defect analysis module 103 is used for traversing and searching the guardrail mask along the column direction and collecting candidate edge points, selecting the inner points of the guardrail boundary through the random sampling consensus algorithm and fitting the boundary line through the least square method; according to all the candidate edge points The distance to the fitting boundary is used to judge whether there is a ...
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