Method for detecting fissure on surface of subway tunnel
A detection method and technology for surface cracks, applied in the field of rail transit, can solve problems such as small edge spacing, and achieve the effect of improving accuracy
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Embodiment 1
[0025] figure 1 It is a schematic diagram of a method for detecting cracks on the surface of a subway tunnel provided by Embodiment 1 of the present invention. Such as figure 1 As shown, the method mainly includes the following steps:
[0026] Step 11. Using a vision system composed of high-speed area array cameras, high-speed image acquisition is performed on the surface of the subway tunnel cavity.
[0027] In the embodiment of the present invention, a vision system installed on a rail car or an electric passenger car is used together with strong light photos to collect high-quality images of the surface of the subway tunnel body.
[0028] Step 12. Perform preprocessing on the collected image to obtain a binarized image.
[0029] In the embodiment of the present invention, grayscale erosion processing is performed on the collected image to obtain a contrast-enhanced grayscale image; then, local histogram stretching processing and local Otsu (Otsu algorithm) segmentation a...
Embodiment 2
[0036] In order to facilitate understanding of the present invention, below in conjunction with Figure 2-6 The present invention will be further described. Such as figure 2 As shown, the detection method of a kind of subway tunnel surface crack that the embodiment of the present invention provides mainly comprises following 1-4 steps:
[0037] 1. High-speed acquisition of tunnel images.
[0038] In the embodiment of the present invention, a vision system composed of a high-speed area array camera is used to collect high-speed images on the surface of the subway tunnel cavity. The vision system can be installed on rail cars or electric passenger cars to realize fast-moving image acquisition, and obtain high-quality tunnel images with strong lighting.
[0039] 2. Tunnel image preprocessing.
[0040] The preprocessing described in the embodiment of the present invention mainly includes three steps: grayscale erosion, local histogram stretching and local Otsu (Otsu algorithm...
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