2020
DOI: 10.3390/app10041290
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An End-To-End Model for Pipe Crack Three-Dimensional Visualization Based on a Cascade Neural Network

Abstract: With the continuous progress of machine vision technology, crack detection in pipelines has been greatly improved. For crack detection in deep holes, inner tubes, and other environments, it is not only necessary to detect the existence of cracks, but also to collect important information regarding the crack detection direction for further analysis. Because shooting with a frontal field of view causes the real side wall images to produce certain distortions, the detection and calibration of cracks requires a ce… Show more

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Cited by 3 publications
(1 citation statement)
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“…In [ 15 ], the authors utilized an active stereo omnidirectional vision sensor to obtain panoramic images of the pipeline’s internal surface. Fang et al [ 16 ] proposed an interesting method that restores the images of pipe walls using images captured from the front view. They addressed the radial distortion issue of the front-view images by employing nonlinear fitting features of a neural network and homemade feature stickers.…”
Section: Introductionmentioning
confidence: 99%
“…In [ 15 ], the authors utilized an active stereo omnidirectional vision sensor to obtain panoramic images of the pipeline’s internal surface. Fang et al [ 16 ] proposed an interesting method that restores the images of pipe walls using images captured from the front view. They addressed the radial distortion issue of the front-view images by employing nonlinear fitting features of a neural network and homemade feature stickers.…”
Section: Introductionmentioning
confidence: 99%