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Tunnel crack area detection method and device

A technology for area detection and tunneling, applied in the field of image recognition, can solve the problem of inaccurate segmentation of tunnel crack areas

Active Publication Date: 2020-06-23
SHIJIAZHUANG TIEDAO UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0005] In view of this, the embodiment of the present invention provides a tunnel crack area detection method and device to solve the problem of inaccurate tunnel crack location and tunnel crack area segmentation in the prior art

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  • Tunnel crack area detection method and device
  • Tunnel crack area detection method and device

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Embodiment Construction

[0060] In the following description, specific details such as specific system structures and technologies are presented for the purpose of illustration rather than limitation, so as to thoroughly understand the embodiments of the present invention. It will be apparent, however, to one skilled in the art that the invention may be practiced in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.

[0061] The overall idea of ​​this application is to take tunnel images with a 4K camera, divide the images into training data sets and test data sets, use Labelme software to accurately calibrate the crack area of ​​the images in the training data set, and use the tunnel crack area provided by the embodiment of this application The detection method performs deep learning model training in the trai...

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Abstract

The invention is applicable to the technical field of image recognition, and provides a tunnel crack area detection method and device. The method comprises the following steps: acquiring a tunnel image; performing convolution operation on the tunnel image through a first preset convolution layer, and performing activation through a preset activation function to obtain a first feature image set; processing the first feature image set by using a feature pyramid network with a preset number of layers to obtain a second feature image set; wavelet decomposition processing and non-subsampling direction filtering processing are performed on the tunnel image for preset times, so that a third feature image set can be obtained; combining the second feature image set and the third feature image set to obtain a combined feature image set; and obtaining a tunnel crack region detection result of the tunnel image based on the image feature information in the combined feature map set. The method can improve the accuracy of crack positioning and tunnel crack area segmentation.

Description

technical field [0001] The invention belongs to the technical field of image recognition, and in particular relates to a method and a device for detecting a tunnel crack area. Background technique [0002] With the rapid development of railway and highway construction, as of the end of 2018, my country has become the country with the most tunnels in the world. Railway tunnels play an important role in railway construction and operation. However, due to the geological environment and large-scale rapid development of the tunnel, tunnel operation will face many challenges, among which tunnel disease is one of the main ones. For the original detection method of the tunnel, it relies more on manual inspection, which may be affected by human factors in the specific inspection. For example, when distinguishing a certain diseased tunnel, different technicians will The discriminant results with large differences are obtained in connection with their own experience, which will have ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06T7/11G06T7/73G06T5/00G06K9/62G06K9/46
CPCG06T7/0004G06T7/11G06T7/73G06T2207/10004G06T2207/20016G06T2207/20081G06T2207/20084G06T2207/30132G06V10/462G06F18/24G06T5/70
Inventor 耿鹏马洪涛吴薇娜罗俊李俊良卢琳
Owner SHIJIAZHUANG TIEDAO UNIV
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