Concrete structure surface defect automatic detection method based on computer vision

A concrete structure and computer vision technology, applied in the field of computer vision, can solve the problems of poor generality and high false detection rate, and achieve the effects of high accuracy, good general performance and high recognition accuracy

Pending Publication Date: 2020-05-08
WUHAN UNIV
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Problems solved by technology

[0003] The purpose of the present invention is to provide an automatic detection method for concrete structure surface defects based on computer vision. In the actual concrete structure detection, this method is based on the video image recognition technology under the framework of deep learning, which fundamentally solves the problem of previous computer vision methods. There are practical problems such as high false detection rate and poor versatility in

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  • Concrete structure surface defect automatic detection method based on computer vision
  • Concrete structure surface defect automatic detection method based on computer vision
  • Concrete structure surface defect automatic detection method based on computer vision

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Embodiment Construction

[0030] In order to better understand the present invention, the technical solutions of the present invention will be further described below in conjunction with examples.

[0031] An automatic detection method for surface defects of concrete structures based on computer vision, including: sampling video data on the time axis to obtain images, in order to reduce the content redundancy between video frames and avoid the resulting calculation time consumption , to improve execution efficiency; the image is input to the deep convolutional neural network model to obtain the position of the defect, the category of the defect and the segmentation effect of the defect.

[0032] Such as figure 1 As shown, the deep convolutional neural network model includes:

[0033] 1. The feature extraction module is used to extract image features;

[0034] Described feature extraction module comprises ResNet50 network module, is used for extracting the feature vector of image.

[0035] ResNet50 d...

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Abstract

The invention belongs to the technical field of computer vision, and particularly relates to a concrete structure surface defect automatic detection method based on computer vision, which comprises the following steps: performing time axis up-sampling on video data to obtain an image, and inputting the image into a deep convolutional neural network model to obtain a defect position, a defect category and a defect segmentation effect. In actual concrete structure detection, the method provided by the invention is based on a video image recognition technology under a deep learning framework, andthe actual problems of high false detection rate, poor universality and the like in the conventional computer vision method are fundamentally solved; from video image data processing and final resultoutput, the method has the advantages of being high in automation degree, good in real-time performance, high in accuracy, good in universality, convenient to upgrade and maintain in the later periodand the like.

Description

technical field [0001] The invention belongs to the technical field of computer vision, and specifically relates to a method for automatically detecting surface defects of concrete structures based on computer vision, which can be widely used in the detection of surface defects of large concrete structures such as cross-river and sea-crossing bridges, urban viaducts, and urban towering buildings. Background technique [0002] With the rapid development of the national economy and the acceleration of the urbanization process, various large-scale concrete structures have sprung up rapidly. Usage requirements. Regular defect detection of concrete structures can provide relevant maintenance departments with effective maintenance data, thereby ensuring the safety of the building during use and improving the maintenance efficiency of the building. However, most of the current domestic inspections of concrete buildings are based on manual methods, which will inevitably bring extre...

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Application Information

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IPC IPC(8): G06T7/00G06T7/11
CPCG06T7/0004G06T7/11G06T2207/10016G06T2207/20081G06T2207/20084G06T2207/30132
Inventor 高鉴李明鹏陈明祥
Owner WUHAN UNIV
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